Digital Commons Network^™

The Legal Risks Posed By Ai Chatbots: Unfair And Deceptive Practices And Other Authorities, Stephanie T. Nguyen, Adam Teitelbaum

Center for Law and the Economy

Growing alarm about existential risks and other harms posed by AI technology have given rise to calls for the government to regulate AI platforms.

This issue brief addresses a related but distinct problem: the use of AI technology by large corporations — including AI platforms themselves — to deploy AI customer-service chatbots1 in ways that may violate existing consumer protection laws. Law enforcers and the plaintiffs’ bar can and should use existing law to stop and deter those violations, and all businesses using AI chatbots should take immediate steps to ensure their AI chatbot practices are compliant with consumer protection …

Study Of A Nonlinear Delayed Parabolic Model For Prion Disease Dynamics With The Unfolded Protein Response, Gangadhara Boregowda, Laurent Pujo-Menjouet, Zhaosheng Feng, Michael R. Lindstrom

School of Mathematical & Statistical Sciences Faculty Publications

Prion diseases are neurodegenerative disorders characterized by the dynamic spread of misfolded toxic proteins in the brain. In this process, the normal cellular prion protein (PrPC) produced by neurons misfolds into a toxic form known as scrapie prion protein (PrPSc). These misfolded proteins propagate through the brain by converting healthy prions into their toxic form. This biological mechanism can be modeled by a system of nonlinear parabolic partial differential equations, accompanied by a nonlinear delayed integral boundary condition. Our primary objective is to establish the existence of nonnegative classical solutions to this system. Furthermore, we derive a priori estimates for …

Adaptive Intelligent H-Infinity Controller Design For Mimo Nonlinear Systems Under Asymmetric Input Saturation, Mohammed Qasim, Hazem I. Ali, Omar Farouq Lutfy

Iraqi Journal of Computers, Communications, Control and Systems Engineering

This paper details the design of a robust adaptive intelligent guaranteed cost H-infinity controller, tailored for MIMO nonlinear systems subject to external disturbances, parametric uncertainties, and asymmetric input saturation constraints. The adaptive intelligent part of the proposed controller consists of a Radial Basis Function Neural Network (RBFNN) with bounded output to respect saturation constraints and a robust adaptive law for RBFNN weights estimation. This part serves to estimate the system's uncertain nonlinearities and external disturbances. The guaranteed cost H-infinity is designed based on Linear Matrix Inequalities (LMIs) to address the system parameter uncertainties and bounded RBFNN estimation errors, as well …

Enhancing Gru With Long-Short Attention: A Case Study Of Saudi Stock Market Prediction, Hussein Samma, Qusay Shihab Hamad, Ali Salem Bin Sama, Adnan Bakather, Khaled Alhashash

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Predicting stock market movements accurately is a challenging task due to the inherent complexity and volatility of financial markets. In recent years, deep learning techniques, particularly the Gated Recurrent Unit (GRU), have shown promising results in financial time series prediction. However, capturing the most relevant information from large volumes of data remains a critical challenge for improving prediction accuracy. This work introduces an attention-enhanced GRU model for forecasting the Saudi stock market. The proposed model integrates attention mechanisms to dynamically prioritize different input patterns, enabling the network to focus on the most relevant information for prediction. Two types of attention …

Improving Performance For Dco-Ofdm Based Vlc Via Convolutional Coding And Viterbi Decoding, Maha F. Shatti, Samir M. Hameed, Atheer A. Sabri

Iraqi Journal of Computers, Communications, Control and Systems Engineering

The reliability of Visible Light Communication (VLC) is affected by several parameters, the most significant being high peak-to-average power ratio(PAPR) and nonlinear distortion. This study presents an adaptive direct current O-OFDM (DCO-OFDM) based VLC system as a solution, which integrates error correction the Convolutional coding and Viterbi decoding (by hard and soft decision methods) with a PAPR reduction technique that combines Vandermonde-like Matrix (VLM) precoding with a nonlinear companding transform (NCT). This proposed system enhances resistance to channel impairments, thereby reducing BER while maintaining the gains of PAPR reduction. Moreover, examined the system under realistic VLC propagation conditions both Line …

Power-Efficient Target Tracking And Coverage In Under-Provisioned Wireless Visual Sensor Networks, Muna M. Jawad

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to their ability to detect the physical environment, directional sensors have attracted a lot of attention in wireless visual sensor networks (WVSN). These sensors perform two key functions: communication and sensing. A WVSN comprises numerous configurable limited fields of view sensors, comprising distinct angular sectors, arranged with multiple targets randomly scattered in the same surrounding region. Therefore, there is a critical need to improve the network's lifetime and reduce power demand while providing complete target coverage. This paper looks at under-resourced visual networks with an inadequate number of sensors to match applications' needs and develops a viable model to …

Cost-Efficient High-Capacity Radio Over Fiber (Rof) Transmission: Integrating Coarse And Dense Wdm Techniques, Hilal A. Fadhil, Fadia N. Hummadi, Feras N. Hasoon, Haider J. Abd, Hussein A. Kazem

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Using Radio over Fiber (RoF) has expanded lately to the point where a key component of it link between central office and base station would be useful from the whole industry. As the market grows towards communication products of ultra-high-speed, like 5G applications, capital expenditure (CapEx) is crucial. The two primary types regarding wavelength division multiplexing (WDM) techniques Dense WDM and Coarse WDM are integrated in the presented work to create cost-effective, new design paradigm for RoF. The suggested system is tested and put into use at 10 Gbps data transmission rate. In addition, it describes how the two systems-based …

A Triple-Verification Framework For Swift, Real-Time Detection Of Anomalous Sensor Readings In Large-Scale Iot Systems, Taha E. Al-Jarakh, Inas Jawad Kadhim, Ayad Al-Dujaili, Eduardo Campos Mercado

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Due to the massive expansion of Internet of Things systems and the variety of anomalous data resulting from faulty sensors, cyberattacks, or communication failures, it has become difficult to handle this type of data. Although current machine learning and statistical analysis techniques offer high accuracy in detecting anomalies, these methods alone are not sufficient for handling massive amounts of data in real-time. Therefore, the idea arose to propose a Triple-Verification Framework to detect and block anomalous data. The first stage of the framework acts as a firewall to block incoming messages from blocklisted/unauthorized sensors or carrying unknown schemes. In the …

A Corpus Linguistics-Driven Hybrid Deep Representation Framework Incorporating Majority Voting For Enhanced Automatic Spoken Language Identification, Lubin Balasubramanian, J. Uthayakumar, Niranjana Kumara M, Sariga Arjunan

Iraqi Journal of Computers, Communications, Control and Systems Engineering

Spoken Language Identification (SLID) is a well-researched area. It has previously been recognized as a crucial first stage in every multi-lingual speech recognition system. Latest developments in artificial intelligence (AI) and deep learning (DL) are used to highly strengthen the performance of SLID systems, allowing them to perform a crucial part in mainstream applications The gathered speaker utterances have been entered into the DL network for training phase. The language equivalent to the great posterior probability is then recognized as the target language. This study introduces an Enhancing Automatic Spoken Language Identification with Corpus Linguistics and Ensemble Deep Representation (EASLI-CLEDR) …

Prevalence Of Vitiligo In East Africa: Systematic Review And Meta-Analysis, Kedir Seid, Chala Getaneh Jaleta, Sintayehu Samuel Lorato, Mitiku Desalegn, Dawit Tesfaye Rundasa, Yohannes Godie Ashebir, Olyad Kuma Getahun, Gebeyehu Lakew, Mathewos Mekonnen Gemmechu, Mulualem Endeshaw Zeleke, Yibeltal Assefa Atalay, Amlaku Nigusie Yirsaw, Eyob Ketema Bogale, Abiy Hailu Tikuneh, Abas Ali Hassen, Eyasu Alem Lake, Tadesse Nigussie, Bushra Bibi, Fikiru Yigezu Y. Jaleta, Abebe Gedefaw Belete, Genanew Kassie Getahun

Research outputs 2022 to 2026

Background: Vitiligo is a chronic skin disorder characterized by the loss of melanocytes, resulting in depigmented macules and patches. No accurate estimate has been made of the prevalence of vitiligo in East Africa.

Objectives: To determine the prevalence of vitiligo in East Africa via a systematic review and meta-analysis of the literature.

Methods: A systematic review and meta-analysis were performed in accordance with the PRISMA guidelines. Eleven articles were retrieved from PubMed/MEDLINE, Embase, Scopus, Google Scholar, Science Direct, Web of Science and African Journals Online. Microsoft Excel was used to extract the data, which were then exported to STATA 17 …

Festivalization As A Tool For Revitalizing Historic Sites The Case Of Maqa’Ad El-Sultan Qaitbay, Cairo, Egypt, Mona Helmy, Sherin Ashraf

Architectural Engineering

Historic sites are vital components of cities' urbanism, embodying distinctive spatial, architectural, and cultural narratives that shape their character. Their significance extends beyond the built environment, arising from the interplay between tangible elements, such as building forms and spatial organization, and intangible socio-cultural aspects. In many historic sites in Egypt and the Arab world, underuse has led to a decline in social vibrancy, reducing their contribution to the urban fabric. To address this issue, global strategies and tools such as adaptive reuse, placemaking, and festivalization have been employed to revitalize historic public spaces. This research explores the potential of festivalization …

The Mirage Of Meta Pixel Code: Redefining Pii In The Era Of Generative Ai, Sophie Venter

Fordham Law Review

Data privacy laws are intended to put consumers in control of whether their identifying data can be sold and used for targeted advertising. However, these laws do not provide adequate protections in the era of generative artificial intelligence (AI). This Note examines one way that existing privacy law permits companies to profit from selling data for targeted advertising without obtaining user consent: transferring video watching data in a pixel code. Some U.S. Courts of Appeals have determined that these data transfers do not sufficiently identify users and the videos they watched to constitute violations of user privacy. This has led …

Revisiting Water Use Household Behavior In Metro Manila: Evidence From The Almost Ideal Demand System Model, Albert E. Lamberte

Angelo King Institute for Economic and Business Studies (AKI)

This study revisits household water use behavior in Metro Manila by estimating residential water demand using the almost ideal demand system (AIDS) and the merged 2021 Family Income and Expenditure Survey-Labor Force Survey. The analysis examines how households respond to price, income, and cross-commodity changes under the two concessionaires, Manila Water (east zone) and Maynilad (west zone). Both have operational environments that differ substantially, particularly in non-revenue water (NRW), tariff structures, and service reliability. Results show that water demand is moderately price-inelastic in both zones. However, households serviced by Maynilad exhibit higher price and income elasticities, reflecting tighter expenditure constraints …

Bard Observer Vol. 25 No. (October 2026), Bard College

Bard Observer, 2020 - 2029

No abstract provided.

State-Aware Fuzzing Of Javascript Engines With Llm-Guided Instrumentation, Wai Kin Wong, Dongwei Xiao, Cheuk Tung Lai, Ping Fan Ke, Shuai Wang

Research Collection School Of Computing and Information Systems

The security of the modern web depends on the correctness of JavaScript (JS) engines, yet these complex systems remain vulnerable to high-impact bugs. A critical limitation of state-of-the-art fuzzers is the coverage plateau: once a fuzzer saturates the control-flow graph, edge coverage loses its ability to guide discovery. Because complex engine behaviors, such as JIT optimization tiers and hidden class transitions, often share identical edge coverage, standard coverage metrics are blind to the distinct internal states required to trigger deep errors. To bridge this gap, we present StateLens, a framework that employs Large Language Models (LLM) to automate the discovery …

Size-Tunable Tellurium Quantum Dots By Glancing Angle Deposition, S. M. Sayem, Salim Hussain, Fernando Maia De Oliveira, Ranjitha Kumarapuram Hariharalakshmanan, Gregory Guisbiers, Tansel Karabacak

Faculty Scholarship

Tellurium has a unique helical crystal arrangement and pronounced anisotropy that influence its electronic and optical properties at the nanoscale. This study reports the synthesis of pure tellurium quantum dots (Te QDs) on silicon wafer using glancing angle deposition (GLAD). Quasi-hemispherical dots with lateral sizes ranging from 9 to 28 nm and vertical dimensions of 6 to 10 nm were produced as a function of the deposition duration. A comparison of the dot sizes with the Bohr radii of the charge carriers indicated a regime of strong to intermediate confinement. Structural analyses confirmed the polycrystalline nature and trigonal phase of …

Arabic Clinical Mental Health Named Entity Recognition Via Distant Supervision: Recurrent Vs. Transformer-Based Architectures, Ali A. Jalil, Rabih Sbera

Polytechnic Journal

Arabic Natural Language Processing (NLP) has made great strides, but the accurate extraction of mental state and physiological symptoms from patient-generated clinical consultations in dialectal Arabic, which is plagued with significant morphological complexity, colloquial noise and an extremely limited number of manually annotated clinical benchmarks, remains a significant challenge. In this work, we propose an end-to-end token-level symptom extraction system that is systematic and grounded in distant supervision paradigm and a strict gold standard evaluation with human verification to ensure real-world clinical generalization. A large weakly labelled corpus of 46,873 Arabic patient questions was created based on a clinical lexicon …

Draft Butte Priority Soils Operable Unit (Bpsou) Silver Bow Creek Conservation Area (Sbcca) Operations And Maintenance (O&M) Plan, Stantec Consulting Services, Inc.

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

A Tribute To Frank Delno Holland, Jr. (1924-2023), Sigma Gamma Epsilon National President (1970-1975), Paleontologist, And Friend, John M. Erickson

The Compass: Earth Science Journal of Sigma Gamma Epsilon

Frank Delno Holland, Jr., was born in Leavenworth, Kansas, on March 6, 1924. All family and friends, including his students and professional acquaintances, knew him as Bud. His parents were Frank D. Holland and Francys Bell Holland. His paternal grandparents, O.B. and Laura Holland were North Dakotans who had homesteaded in Sargent County during the 1880s, but had relocated to Kansas in 1903. Bud had a rural upbringing on the outskirts of Leavenworth, graduating in 1942 from Leavenworth High school. It seemed natural that he would follow in his father’s footsteps by attending the University of Kansas (KU) so Bud …

State: The Magazine Of Illinois State University, Fall 2026, Illinois State University, University Marketing And Communications

State: The Magazine of Illinois State University (1999-present)

Illinois State University alumni magazine

Assessing The Co-Benefits Of Housing And Transportation Investments In Prohousing Designated Jurisdictions, Hongwei Dong

Mineta Transportation Institute

In response to California's ongoing housing affordability crisis, state and local governments have adopted a range of prohousing policies aimed at reducing barriers to housing production and promoting the integration of housing with transportation. This study examines two distinct but related dimensions of prohousing policies in California. One concerns the Prohousing Designation Program (PDP) (established by the 2019–2020 Budget Act), analyzing the adoption and implementation of prohousing policies in 56 California cities that received Prohousing Designation. The other examines recent state and local policy shifts aimed at promoting affordable housing in transit-rich areas. The study uses a mixed-methods research design, …

Analysis And Design Of Multi-Winding Current Ballasted Magnetics For Integrated Dc-Dc Conversion, Kishalay Datta

Dartmouth College Ph.D Dissertations

Power conversion circuits have become a bottleneck in terms of reducing the size and cost of modern electronic systems in a vast number of applications ranging from personal devices, to automotive systems, to data centers. This has motivated designs at higher frequencies where smaller passive components can be used. Unfortunately, magnetic components scale poorly to smaller dimensions. In addition, the AC resistance of magnetic components deteriorates due to current crowding effects at high frequencies. This has resulted in fully- integrated power converters with planar magnetic components having efficiencies lower than what may be theoretically achieved. In this work, we investigate …

Alfred Russel Wallace Notes 43. Alfred Russel Wallace’S Social Environment And Moral Progress., David Stack, Charles H. Smith Editor

Faculty/Staff Personal Papers

Alfred Russel Wallace’s Social Environment and Moral Progress (1913) was the last book he wrote and one of the most powerful statements of his thought and beliefs. As with his Revolt of Democracy (1913), written before but published after Social Environment and Moral Progress, the work finds Wallace passionate in his advocacy of social and economic reform. Despite his advanced age (Wallace turned 90 in January 1913), the book is deeply engaged with contemporary controversies, including the rise of labor, arguments against eugenics, and debates around the social and political status of women. What distinguishes Wallace’s text is that he …

Line Of Sight Lighting Effect In Dark Environment And Its Impact On Interactive Horror Game Experience, Hamzah Asyrani Sulaiman, Fuyen Heng

Malaysian Journal of Computing (MJoC)

Lighting effects in dark environments represent a fundamental psychological mechanism in horror game design, directly shaping player immersion, emotional tension, and the quality of interactive experience. Although Line of Sight (LoS) technology has been widely adopted across many game genres, empirical investigations examining how LoS-based dynamic lighting specifically affects player engagement, usability, and visual aesthetic perception within single-player horror puzzle contexts remain scarce. This paper presents the design, development, and user evaluation of “No One Left”, a three-dimensional top-down horror puzzle game developed using Unreal Engine 4, which systematically employs LoS-based lighting mechanics within a dark environment to restrict player …

Machine Learning-Based Mental Health Risk Prediction And Behavioural Clustering Among Malaysian Undergraduates, Norsyela Muhammad Noor Mathivanan, Debbie Yong Xi Foo, Gerard Soon Lee Chong, Siti Fazilah Shamsudin, Marizkays P. Jamison

Malaysian Journal of Computing (MJoC)

Mental health issues among undergraduate students have become increasingly prevalent, affecting emotional well-being, academic performance, and overall quality of life. The growing number of students experiencing stress, anxiety, and depression highlights the need for effective predictive models to support early risk identification and personalized intervention strategies. This study investigates the performance of several machine learning approaches, including Logistic Regression (LR), Random Forest (RF), Gradient Boosting, LightGBM, Extra Trees, XGBoost, Support Vector Classifier (SVC), and a stacked ensemble model for predicting mental health risk among Malaysian undergraduate students. The study utilizes a dataset comprising demographic, academic, lifestyle, and psychological assessment attributes …

Malaysia Tech Stock Forecasting Using Arima: A Comparative Analysis With Kalman Filter Noise Optimization, Sarah Nadirah Mohd Johari, Ahmad Irfan Mohd Sukeri, Restu Ananda Putra, Ahmad Nur Azam Ahmad Ridzuan

Malaysian Journal of Computing (MJoC)

Forecasting stock prices in Malaysia's technology sector is difficult due to market noise. To mimic market behavior, many models have been developed and gradually improved with new algorithms and machine learning techniques. Relying on a single model often has drawbacks, so hybrid models were introduced to improve prediction stability. This study used a time series method, Autoregressive Integrated Moving Average (ARIMA) that has been proven to be reliable in forecasting various types of data. However, the ARIMA model often struggles with handling nonlinear and noisy data; thus, hybrid integration of the Kalman Filter was introduced to help reduce noise. The …

Turning Ontologies Into Vectors: Embedding Malay Ontological Knowledge For Smarter Machine Learning, Zayanah Zafirah Zulkipli, Ruhaila Maskat, Noor Hasimah Ibrahim Teo, Jie Zhang

Malaysian Journal of Computing (MJoC)

This conceptual study proposes a three-layer methodological framework for representing Malay ontological knowledge in continuous vector spaces and integrating ontology-derived representations with machine-learning models. The framework comprises an Ontology Layer, an Embedding Layer, and an Integration Layer. Its contribution is not a new ontology-embedding algorithm rather, it provides a Malay-oriented methodological organization that links ontology construction, embedding-method selection, symbolic-subsymbolic fusion, ontology-guided consistency checking, and downstream evaluation. In the present study, the ontology layer is represented through a prototype Malay linguistic ontology and its class hierarchy and knowledge graph, whereas the embedding, integration, consistency-checking, and downstream evaluation stages are proposed components …

A Fuzzy Logic Decision Support System For University Student Dropout Assessment, Adam Aiman A Hamid, Harliza Mohd Hanif, Siti Rahimah Batcha, Nur Zafirah Mohd Sidek, Noratika Nordin, Norain Alwi

Malaysian Journal of Computing (MJoC)

Student dropout continues to be an issue in universities, which has a negative impact on the academic performance of students and the reputation of educational institutions. Since the dropout decision is affected by multiple factors like academic performance, financial situation, stress, and self-motivation, the status of these factors can be highly uncertain, subjective, and conventional assessment methods cannot consider this impreciseness. This study designed a fuzzy logic–based decision support system approach to account for the risk of student dropout in a flexible and human-like way. The purpose of this study was to assess the potential risk of a student dropout …

Comparative Machine Learning Prediction Of Carbon Monoxide Levels And Contributing Factors In Shah Alam, Farzana Zubaidi, Norshahida Shaadan, Septia Devi Prihastuti Yasmirullah

Malaysian Journal of Computing (MJoC)

Carbon monoxide (CO) pollution is a major environmental and public health concern because it is colourless and odourless and is produced mainly by incomplete combustion from vehicles, industries, and household sources. Accurate prediction of CO levels and identification of key contributing factors can support early warning and targeted mitigation strategies. This study compared eight machine-learning regression models—Support Vector Regression (SVR), Random Forest Regression (RFR), Decision Tree Regression (DTR), K-Nearest Neighbours (KNN), CatBoost, XGBoost, LightGBM, and Neural Network Regression (NNR)—using daily air-quality data from the Department of Environment Malaysia for 2018–2023. The dataset comprised 42 input features representing air pollutants, meteorological …

Iot-Enabled Smart Durian Harvesting: An Integrated Platform For Real-Time Orchard Monitoring And Sustainable Harvest Management, Norisan Abd Karim, Nur Carmilla Abdullah Muhammad Shafiq, Nur’Aina Daud, Syibrah Naim, Syaheerah Lebai Lutfi

Malaysian Journal of Computing (MJoC)

Durian harvesting requires timely monitoring to ensure that fallen fruits are collected promptly, thereby reducing quality deterioration and potential economic losses. Traditional orchard monitoring relies heavily on manual inspection, making the process time-consuming, labour-intensive, and inefficient, particularly in large orchards. The Internet of Things (IoT) technology has been widely used in smart agriculture to manage orchards, but there are very few existing systems that combine real-time durian fall detection with a mobile application that sends immediate notifications, automatic image capture of fall events, and orchard management functions. This study develops an Integrated IoT-Based Smart Orchard Platform for real-time durian harvest …