Physical Sciences and Mathematics Commons^™

The Role Of Ammonia In Atmospheric New Particle Formation And Implications For Cloud Condensation Nuclei, Arshad Arjunan Nair

Legacy Theses & Dissertations (2009 - 2024)

Atmospheric ammonia has received recent attention due to (a) its increasing trend across various regions of the globe; (b) the associated direct and indirect (through PM2.5) effects on human health, the ecosystem, and climate; and (c) recent evidence of its role in significantly enhancing atmospheric new particle formation (NPF or nucleation) rates. The mechanisms behind nucleation in the atmosphere are not fully understood, although over the last decade there have been significant developments in our understanding. This dissertation aims at improving our understanding of atmospheric ammonia in the atmosphere, its spatiotemporal variability, its role in atmospheric new particle formation, and …

Brain Tumor Detection From Mri Images With Using Proposed Deep Learningmodel: The Partial Correlation-Based Channel Selection, Atinç Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

A brain tumor is an abnormal growth of a mass or cell in the brain. Early diagnosis of the tumor significantly increases the chances of successful treatment. Artificial intelligence-based systems can detect the tumor in early stages. In this way, it could be possible to detect a tumor and resolve this problem that may endanger human life early. In the study, the partial correlation-based channel selection formula was presented that allowed the selection of the most prominent feature that differs from the other studies in the literature. Additionally, the multi-channel convolution structure was proposed for the feature network phase of …

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 …

Chaos In Metaheuristic Based Artificial Intelligence Algorithms:A Short Review, Gökhan Atali, İhsan Pehli̇van, Bi̇lal Gürevi̇n, Hali̇l İbrahi̇m Şeker

Turkish Journal of Electrical Engineering and Computer Sciences

Metaheuristic based artificial intelligence algorithms are commonly used in the solution of optimization problems. Another area -besides engineering systems- where chaos theory is widely employed is optimization problems. Being applied easily and not trapping in local optima, chaos-based search algorithms have attracted great attention. For example, it has been reported that when random number sequences generated from different chaotic systems are replaced with parameter values in bioinspired and swarm intelligence algorithms, an increase in the performance of metaheuristic algorithms is observed. Many scientific studies on developing hybrid algorithms in which metaheuristic algorithms and chaos theory are used together are already …

Interpretable, Not Black-Box, Artificial Intelligence Should Be Used For Embryo Selection, Michael Anis Mihdi Afnan, Yanhe Liu, Vincent Conitzer, Cynthia Rudin, Abhishek Mishra, Julian Savulescu, Masoud Afnan

Research outputs 2014 to 2021

Artificial intelligence (AI) techniques are starting to be used in IVF, in particular for selecting which embryos to transfer to the woman. AI has the potential to process complex data sets, to be better at identifying subtle but important patterns, and to be more objective than humans when evaluating embryos. However, a current review of the literature shows much work is still needed before AI can be ethically implemented for this purpose. No randomized controlled trials (RCTs) have been published, and the efficacy studies which exist demonstrate that algorithms can broadly differentiate well between ‘good-’ and ‘poor-’ quality embryos but …

Understanding And Predicting Retractions Of Published Work, Sai Ajay Modukuri, Sarah Rajtmajer, Anna Cinzia Squicciarini, Jian Wu, C. Lee Giles

Computer Science Faculty Publications

Recent increases in the number of retractions of published papers reflect heightened attention and increased scrutiny in the scientific process motivated, in part, by the replication crisis. These trends motivate computational tools for understanding and assessment of the scholarly record. Here, we sketch the landscape of retracted papers in the Retraction Watch database, a collection of 19k records of published scholarly articles that have been retracted for various reasons (e.g., plagiarism, data error). Using metadata as well as features derived from full-text for a subset of retracted papers in the social and behavioral sciences, we develop a random forest classifier …

Increasing The Value Of Information During Planning In Uncertain Environments, Gaurab Pokharel

Honors Papers

Prior studies have demonstrated that for many real-world problems, POMDPs can be solved through online algorithms both quickly and with near optimality [10, 8, 6]. However, on an important set of problems where there is a large time delay between when the agent can gather information and when it needs to use that information, these solutions fail to adequately consider the value of information. As a result, information gathering actions, even when they are critical in the optimal policy, will be ignored by existing solutions, leading to sub-optimal decisions by the agent. In this research, we develop a novel solution …

Adoption Of Artificial Intelligence (Ai) In Local Governments: An Exploratory Study On The Attitudes And Perceptions Of Officials In A Municipal Government In The Philippines, Charmaine B. Distor, Odkhuu Khaltar, M. Jae Moon

Journal of Public Affairs and Development

Emerging technologies like artificial intelligence (AI) have been instrumental in transforming governments in recent years, which is why several agencies worldwide have integrated them into their governance strategies. One of the countries that have paid attention to the potential of AI is the Philippines, which launched its national AI roadmap in 2021. This study investigated the perceived acceptance and adoption of AI in the Municipality of Carmona located in the Province of Cavite. Following the combined constructs from the Technology Acceptance Model (TAM) and Unified Theory of Acceptance and Use of Technology (UTAUT), perception data were gathered from among Carmona’s …

Food/Non-Food Classification Of Real-Life Egocentric Images In Low- And Middle-Income Countries Based On Image Tagging Features, Guangzong Chen, Wenyan Jia, Yifan Zhao, Zhi-Hong Mao, Benny Lo, Alex K Anderson, Gary Frost, Modou L Jobarteh, Megan A Mccrory, Edward Sazonov, Matilda Steiner-Asiedu, Richard S Ansong, Thomas Baranowski, Lora Burke, Mingui Sun

Children’s Nutrition Research Center Staff Publications

Malnutrition, including both undernutrition and obesity, is a significant problem in low- and middle-income countries (LMICs). In order to study malnutrition and develop effective intervention strategies, it is crucial to evaluate nutritional status in LMICs at the individual, household, and community levels. In a multinational research project supported by the Bill & Melinda Gates Foundation, we have been using a wearable technology to conduct objective dietary assessment in sub-Saharan Africa. Our assessment includes multiple diet-related activities in urban and rural families, including food sources (e.g., shopping, harvesting, and gathering), preservation/storage, preparation, cooking, and consumption (e.g., portion size and nutrition analysis). …

Algorithmic Responsibility, Algorithmic Bias, Darla Jackson

Other Faculty Publications

No abstract provided.

Applied Machine Learning In Extrusion-Based Bioprinting, Shuyu Tian

Theses and Dissertations

Optimization of extrusion-based bioprinting (EBB) parameters have been systematically conducted through experimentation. However, the process is time and resource-intensive and not easily translatable across different laboratories. A machine learning (ML) approach to EBB parameter optimization can accelerate this process for laboratories across the field through training using data collected from published literature. In this work, regression-based and classification-based ML models were investigated for their abilities to predict printing outcomes of cell viability and filament diameter for cell-containing alginate and gelatin composite hydrogels. Regression-based models were investigated for their ability to predict suitable extrusion pressure given desired cell viability when keeping …

A Novel Method For Soc Estimation Of Li-Ion Batteries Using A Hybrid Machinelearning Technique, Eymen İpek, Murat Yilmaz

Turkish Journal of Electrical Engineering and Computer Sciences

The battery system is one of the key components of electric vehicles (EV) which has brought groundbreaking technologies. Since modern EVs have mostly Li-ion batteries, they need to be monitored and controlled to achieve safe and high-performance operation. Particularly, the battery management system (BMS) uses complex processing systems that perform measurements, estimation of the battery states, and protection of the system. State of charge (SOC) estimation is a major part of these processes which defines remaining capacity in the battery until the next charging operation as a proportion to the total battery capacity. Since SOC is not a parameter that …

Cybersecurity Leaders: Knowledge Driving Human Capital Development, Sharon L. Burton

Publications

Cybersecurity leaders must be able to use critical reading and thinking skills, exercise judgment when policies are not distinct and precise, and have the knowledge, skills, and abilities to tailor technical and planning data to diverse customers’ levels of understanding. Ninety-three percent of cybersecurity leaders do not report directly to the chief operating officer. While status differences influence interactions amid groups, attackers are smarter. With the aim of protecting organizations and reducing risk, knowledge about security must increase. Understanding voids are costly and increased breach chances are imminent. Burning questions exist. What are needed technological learnings for cybersecurity leaders to …

The Value Of Humanization In Customer Service, Yang Gao, Huaxia Rui, Shujing Sun

Research Collection School Of Computing and Information Systems

As algorithm-based agents become increasingly capable of handling customer service queries, customers are often uncertain whether they are served by humans or algorithms, and managers are left to question the value of human agents once the technology matures. The current paper studies this question by quantifying the impact of customers' enhanced perception of being served by human agents on customer service interactions. Our identification strategy hinges on the abrupt implementation by Southwest Airlines of a signature policy, which requires the inclusion of an agent's first name in responses on Twitter, thereby making the agent more humanized in the eyes of …

A Web-Based Ai Assistant Application Using Python And Javascript, Viet Le, Tej Bahadur, Jainee Shah, Roushan Ara

School of Professional Studies

Our research is mainly based on a chatbot which is powered by Artificial Intelligence. Nowadays, Artificial Intelligence assistants such as Apple’s Siri, Google’s Now and Amazon’s Alexa are currently fast-growing and widely integrated with many smart devices. These assistants are built with the primary purpose of being personal assistants for every individual user in certain contexts. In this research, we would highlight the development process of the chatbots, features, problems, case studies and limitations.

This research delivers the information, helps developers to build answer bots and integrate chatbots with business accounts. The aim is to assist users and allow transactions …

Artificial Intelligence In A Main Warehouse In Panasonic: Los Indios, Texas, Edison Antonio Trejo Hernandez

Theses and Dissertations

The Panasonic Company warehouse is located in Los Indios Texas. The warehouse presents the limitation of the great distances between its headquarters and the Main Warehouse for supplying the branches and main customers, which requires a considerable amount of time to maintain effective communication in the inventory area. In addition, during an online review, it can be confirmed that the website is disabled, contradicting its corporate policy.

The structure of the thesis proposal is arranged in four chapters from the Introduction, Statement of the Problem and Purposes; Previous Studies and Definition of the literature; the Research Methodology and the resources …

Neural Network Development In An Artificial Intelligence Gomoku Program, David Garcia

Theses and Dissertations

The game of Gomoku, also called Five in a Row, is an abstract strategy board game. The Gomoku program is constructed upon an algebraic monomial theory to aid values for each possible move and estimate chances for the artificial intelligence program to accomplish a winning path for each move and rounds. With the utilization of the monomial theory, winning configurations are successfully converted into monomials of variables which are represented on board positions. In the artificial intelligence program, an arduous task is how to perform the present configuration of the Gomoku game along with the past moves of the two …

Computational Cognition And Deep Learning, Andy Malinsky

The Compass

No abstract provided.

New Methods For Deep Learning Based Real-Valued Inter-Residue Distance Prediction, Jacob Barger

Theses

Background: Much of the recent success in protein structure prediction has been a result of accurate protein contact prediction--a binary classification problem. Dozens of methods, built from various types of machine learning and deep learning algorithms, have been published over the last two decades for predicting contacts. Recently, many groups, including Google DeepMind, have demonstrated that reformulating the problem as a multi-class classification problem is a more promising direction to pursue. As an alternative approach, we recently proposed real-valued distance predictions, formulating the problem as a regression problem. The nuances of protein 3D structures make this formulation appropriate, allowing predictions …

Deep-Learning-Based App Sensitive Behavior Surveillance For Android Powered Cyber-Physical Systems, Haoyu Ma, Jianwen Tian, Kefan Qiu, David Lo, Debin Gao, Daoyuan Wu, Chunfu Jia, Thar Baker

Research Collection School Of Computing and Information Systems

Android as an operating system is now increasingly being adopted in industrial information systems, especially with Cyber-Physical Systems (CPS). This also puts Android devices onto the front line of handling security-related data and conducting sensitive behaviors, which could be misused by the increasing number of polymorphic and metamorphic malicous applications targeting the platform. The existence of such malware threats therefore call for more accurate identification and surveillance of sensitive Android app behaviors, which is essential to the security of CPS and IoT devices powered by Android. Nevertheless, achieving dynamic app behavior monitoring and identification on real CPS powered by Android …

Artificial Intelligence: A Prospective Or Real Option For Education?, Maha Sourani

Al Jinan الجنان

The education sector is grappling with a plethora of challenges that have compelled scholars and practitioners to begin looking for a solution. Artificial intelligence (AI) is among the proposed solutions that is having significant attention lately. However, its adoption in the education sector remains low because of challenges, such as lack of proper trials, testing, and recommendation for its applicability in the sector. This article seeks to explore the role and potentiality of AI in improving education. A systematic review design is used for this purpose. The methodology corresponds with the rapid survey protocol of Khangura (2012) which provides an …

The Future Of Work Now: Ai-Driven Transaction Surveillance At Dbs Bank, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

Chess As A Testing Grounds For The Oracle Approach To Ai Safety, James D. Miller, Roman Yampolskiy, Olle Häggström, Stuart Armstrong

Faculty and Staff Scholarship

To reduce the danger of powerful super-intelligent AIs, we might make the first such AIs oracles that can only send and receive messages. This paper proposes a possibly practical means of using machine learning to create two classes of narrow AI oracles that would provide chess advice: those aligned with the player's interest, and those that want the player to lose and give deceptively bad advice. The player would be uncertain which type of oracle it was interacting with. As the oracles would be vastly more intelligent than the player in the domain of chess, experience with these oracles might …

Research On Geographical Battlefield Environment Model Facing Autonomous Platform, You Xiong, Jiangpeng Tian

Journal of System Simulation

Abstract: Battlefield environment model is an abstraction and description of the complex battlefield environment for specific needs. It supports the research and application of the nature and evolution of the battlefield environment. However, the existing battlefield environment model is mainly oriented to human war activities to describe the battlefield environment,and lacks the design for unmanned autonomous platforms. A multi-level battlefield environment model structure which couples the advantages of humans and machines is proposed, which can give full play to the machine's rapid numerical calculation capabilities at the geometric and feature levels, as well as human cognitive experience at the element, …

The Future Of Work Now: The Multi-Faceted Mall Security Guard At A Multi-Faceted Jewel, Thomas H. Davenport, Steven M. Miller

Research Collection School Of Computing and Information Systems

One of the most frequently-used phrases at business events these days is “the future of work.” It’s increasingly clear that artificial intelligence and other new technologies will bring substantial changes in work tasks and business processes. But while these changes are predicted for the future, they’re already present in many organizations for many different jobs. The job and incumbents described below are an example of this phenomenon. Steve Miller of Singapore Management University and I co-authored the story.

An Ecosystem Approach To Ethical Ai And Data Use: Experimental Reflections, Mark Findlay, Josephine Seah

Research Collection Yong Pung How School Of Law

While we have witnessed a rapid growth of ethics documents meant to guide artificial intelligence (AI) development, the promotion of AI ethics has nonetheless proceeded with little input from AI practitioners themselves. Given the proliferation of AI for Social Good initiatives, this is an emerging gap that needs to be addressed in order to develop more meaningful ethical approaches to AI use and development. This paper offers a methodology-a 'shared fairness' approach-aimed at identifying AI practitioners' needs when it comes to confronting and resolving ethical challenges and to find a third space where their operational language can be married with …

Predictive Insights For Improving The Resilience Of Global Food Security Using Artificial Intelligence, Meng Leong How, Yong Jiet Chan, Sin Mei Cheah

Research Collection Lee Kong Chian School Of Business

Unabated pressures on food systems affect food security on a global scale. A human-centric artificial intelligence-based probabilistic approach is used in this paper to perform a unified analysis of data from the Global Food Security Index (GFSI). The significance of this intuitive probabilistic reasoning approach for predictive forecasting lies in its simplicity and user-friendliness to people who may not be trained in classical computer science or in software programming. In this approach, predictive modeling using a counterfactual probabilistic reasoning analysis of the GFSI dataset can be utilized to reveal the interplay and tensions between the variables that underlie food affordability, …

Application Of Artificial Intelligence And Geographic Information System For Developing Automated Walkability Score, Md Mehedi Hasan

Dissertations

Walking is considered as one of the major modes of active transportation, which contributes to the livability of cities. It is highly important to ensure walk friendly sidewalks to promote human physical activities along roads. Over the last two decades, different walk scores were estimated in respect to walkability measures by applying different methods and approaches. However, in the era of big data and machine learning revolution, there is still a gap to measure the composite walkability score in an automated way by applying and quantifying the activityfriendliness of walkable streets. In this study, a street-level automated walkability score was …

Deep Learning For Remote Sensing Image Processing, Yan Lu

Computational Modeling & Simulation Engineering Theses & Dissertations

Remote sensing images have many applications such as ground object detection, environmental change monitoring, urban growth monitoring and natural disaster damage assessment. As of 2019, there were roughly 700 satellites listing “earth observation” as their primary application. Both spatial and temporal resolutions of satellite images have improved consistently in recent years and provided opportunities in resolving fine details on the Earth's surface. In the past decade, deep learning techniques have revolutionized many applications in the field of computer vision but have not fully been explored in remote sensing image processing. In this dissertation, several state-of-the-art deep learning models have been …

From The Tree Of Knowledge And The Golem Of Prague To Kosher Autonomous Cars: The Ethics Of Artificial Intelligence Through Jewish Eyes, Nachshon Goltz, John Zeleznikow, Tracey Dowdeswell

Research outputs 2014 to 2021

This article discusses the regulation of artificial intelligence from a Jewish perspective, with an emphasis on the regulation of machine learning and its application to autonomous vehicles and machine learning. Through the Biblical story of Adam and Eve as well as Golem legends from Jewish folklore, we derive several basic principles that underlie a Jewish perspective on the moral and legal personhood of robots and other artificially intelligent agents. We argue that religious ethics in general, and Jewish ethics in particular, show us that the dangers of granting moral personhood to robots and in particular to autonomous vehicles lie not …