Digital Commons Network^™

Dose-Dependent Effects Of Exosomes On The Viability And Differentiation Of Human Dental Pulp Stem Cells, Tsui-Hsien Huang

Articles in Press

No abstract provided.

System And Method For Temporally-Correct Point-In-Time Embedding Reconstruction From Append-Only Accumulator Delta Logs, Durga S. Kala, Xinrong Huang, Nishanth Telukunta, Sreekanth Kanichetty

Defensive Publications Series

A system (200) for point-in-time reconstruction of time-decayed behavioral embedding accumulator states for payment entities includes an append-only accumulator delta log (202) that records, for each accumulator update event, an entity identifier, an exact authorization timestamp, a D-dimensional embedding delta, a pre-computed exponential decay factor, and the resulting accumulator weight. A checkpoint store (204) periodically snapshots the accumulator state including a decayed sum, a total weight, and a timestamp for each entity. A reconstruction engine (206) reads the latest checkpoint prior to a query timestamp, replays all delta log entries for the entity with timestamp strictly less than the query …

Decoupled Pricing And Fulfillment Arbitrator For Multi-Destination Agentic Commerce Systems, Richa Gupta

Defensive Publications Series

A decoupled pricing and fulfillment arbitrator extends the Universal Commerce Protocol (UCP) to maintain volume-based discounts for e-commerce orders shipped to multiple destinations. The system operates through a two-phase cryptographic handshake, where the arbitrator first validates the total item quantity in a cart to secure a global price lock from a merchant’s application programming interface (API). The arbitrator then atomizes the single order into multiple, concurrent fulfillment requests, one for each distinct shipping address. By embedding a cryptographic bulk token into each parallel request, the arbitrator instructs the merchant’s system to bypass standard single-destination validation rules and apply the pre-approved …

Cpeven‑Ω2.0 Caldwell Planetary Environmental Verification & Early‑Warning Network, Michael Victor Caldwell Mr.

Defensive Publications Series

CPEVEN‑Ω2.0 is a fully open, modular, multi‑physics environmental measurement and verification architecture designed for global deployment. It integrates reference‑grade sensors, distributed open nodes, multi‑physics correlation, artifact detection, uncertainty‑aware fusion, satellite/model comparison, source attribution, and experimental technology validation into one unified system.

CPEVEN‑Ω2.0 is not a sensor.

It is not a weather station.

It is not a model.

It is not a prediction engine.

It is a planetary environmental verification network that preserves raw measurements, validates experimental technologies, correlates multi‑domain signals, and produces reproducible environmental intelligence.

Every module is open hardware.

Every interface is documented.

Every measurement is traceable.

Every experimental …

Remote Control Using Render Buffer Accessibility Extraction, Inductively Powered Electrophoretic Keycaps, And An Ultra-Wideband Pointing Latch, Stenal P. Jolly

Defensive Publications Series

Streaming applications on a smart television often render an interface into a single hardware-accelerated graphics surface.  A native accessibility engine may treat that surface as one opaque node, and printed remote keycaps do not follow the content on screen.  A remote control system addresses these limitations by extracting geometry and text directly from a graphics processing unit (GPU) render buffer of a host computing device.  The system rebuilds a virtual accessibility tree once per render frame.  Compact per-key updates travel over a low-energy wireless link to electrophoretic keycap displays, and inductive power regulation holds each keycap display at a steady …

Routability-Aware Decoupling Capacitor Insertion Using Trial-Route Lookups And Linear Programming, Prateek Pendyala

Defensive Publications Series

Dynamic IR drop, a transient loss of supply voltage proportional to current (I) and resistance (R), can erode timing margins on advanced process nodes.  Decoupling capacitors (decaps) inserted near cells with high switching activity can suppress the drop.  The regions that need decaps, however, tend toward heavy routing congestion, so a newly placed decap can trigger detailed routing design rule violations (DRVs).  An example routability-aware method selects decap locations and bounded cell moves through a linear program built from measured routing data.  The method models cell currents as rectangular envelopes over binned time, computes a missing charge from a charge …

A Load-Bearing, Fluid-Mediated Robotic Joint Architecture Combining Variable-Geometry Friction Interlocks With Passive Multi-Stage Granular Jamming Inside A Tensegrity Compression Frame, Volodymyr Kotegov

Defensive Publications Series

This paper describes the QUINTO-CMC modular articulation architecture, built to hold high structural loads in contaminated or corrosive operating environments while cutting static holding power to a minimal telemetry-only draw. The system replaces high-maintenance, actively powered joints with an unpowered, field-replaceable cartridge that locks mechanically under zero electrical load. The physical joint module weighs no more than 1.75 kg. Static holding draw is limited to 18–25 W for telemetry and monitoring alone — the mechanical lock itself needs no electrical power. Three kinematically uncoupled passive locking layers trigger in sequence during pressure drops or sudden fluid loss. The primary retention …

Two‑Phase Trust‑Region Constraint Programming With Dynamic Bounds Scaling For Macro Legalization And Alignment, Vijayavelu S, Amit Saluja, Surya Barik, Arijit Hazra

Defensive Publications Series

Legalizing a mixed‑size layout that holds large hard macro blocks together with millions of standard cells becomes difficult at advanced technology nodes, where mismatched technology grids and zero‑slack boundaries leave narrow room for movement.  Prior approaches bound macro movement with one static displacement limit, so a tight limit can leave macros out of alignment and a loose limit can deadlock a discrete engine.  Disclosed is a two‑phase method that separates legalization from alignment.  A first phase carries hard feasibility rules without an alignment objective and returns a legal coordinate set.  A bounds scaling module then sizes a search window for …

Method And System For Consumer-Specific Attribute Filtering In Distributed Message Brokers, Soumendra Kumar Mishra, Mansi Singh, Ravi Shanker Kumar Sinha, Amitabh Ranjan, Katyayani Kiranmayee Kolluru, Sumit Kumar

Defensive Publications Series

A system for consumer-specific attribute filtering in a distributed message broker environment is provided. The system includes an attribute subscription registry configured to store a consumer identifier, a topic identifier, and a list of permitted attribute paths for each consumer. The system includes a producer interface configured to publish a canonical message payload containing a plurality of attributes to a message broker, compute an Attribute Location Index during serialization that maps each attribute name to byte offset boundaries within a serialized message body, and attach the Attribute Location Index as a message header. The system includes the message broker configured …

Rule Based Pre-Execution Validation Of Financial Transactions With Generative Anomaly Explanations, Shalini Jha, Farhan Rawani, Bhaskar Mangalampalli, Alba Campus, Sanhitha Seerapu, Millie Martin, Arib Shan, Tilottama Basu, Amogh Badugu, Sai Krishna, Ramya Karyampudi

Defensive Publications Series

Financial transaction processing systems, for example in payroll, can face challenges where validation is reactive, leading to the late discovery of complex discrepancies after payments are executed. A system and method are described for pre-execution validation of financial transactions. The system can function as a validation layer that applies business rules to batches of transaction data using techniques such as set-based processing. This approach can identify potential anomalies across large datasets before execution. For detected anomalies, a generative model can produce a human-readable explanation detailing a potential rule violation and the associated data. This pre-execution identification and contextualization of potential …

Continuous Dimension Extraction For Semantic Product Organization, Nathan Grabaskas

Defensive Publications Series

Systems for organizing products on digital commerce platforms can be limited by rigid taxonomies that may not capture nuanced attributes, and some high-dimensional vector representations can lack interpretability. A computational framework can transform product information into a semantically organized and navigable space. The framework can encode products into high-dimensional vectors and then employ two parallel processes. One path may use clustering algorithms and generative language models to group products into labeled sub-archetypes. A second path may use non-linear dimensionality reduction followed by an iterative principal component analysis to extract and label continuous trade-off axes from the data. The resulting clusters …

Steering Generative Ai Responses By Predicting User Intentions Using Slms And Behavioral Telemetry, Rachit Mathur, Payal Shah

Defensive Publications Series

Current conversational AI systems rely on monotonic streaming, requiring users to wait for complete responses before correcting misinterpretations. This disclosure describes a bifurcated dual-dispatch architecture that steers generative AI outputs mid-stream. By pairing a localized Small Language Model (SLM) shadow parser with a high-capacity frontier LLM, the system dynamically analyzes real-time client-side behavioral telemetry - including keystroke dwell times, backspace mutation ratios, and paste metadata to predict user intent and cognitive friction. When volatile semantic nodes or potential intent mismatches are detected, the SLM executes pre-emptive mitigations by tuning inference hyperparameters (such as temperature) or surfacing non-blocking, inline "intent chips" …

Portrait: Holistic Data Visualization Using Neural Networks, Chayan Maitra

Doctoral Theses

With the exponential growth of complex data across domains, effective visualization has become increasingly crucial for understanding relationships hidden within high-dimensional spaces. However, existing visualization techniques often struggle to effectively capture and represent such high-dimensional data. Motivated by this challenge, we have developed NeuroDAVIS, a neural network model designed to visualize high-dimensional data by extracting meaningful latent representations through deep feature extraction. While NeuroDAVIS has successfully addressed the visualization aspect, we have soon recognized the necessity of identifying the most relevant features that contribute to the visualization and downstream analysis. To address this issue, we have extended our framework and …

Midweek Memo, Georgia Southern University

Midweek Memo

• Applaud 
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• Share 
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• Around the Nest

Challenges, Trends, And The Role Of Lstm In Ai-Based Predictive Maintenance Of Electrolyzers For Solar Hydrogen Systems: A Review, Yani Koerniawan Kuatno, Muhamad Zahim Sujod

Turkish Journal of Electrical Engineering and Computer Sciences

The transition toward low-carbon energy systems has increased interest in hydrogen as a clean energy carrier, with solar-driven water electrolysis emerging as a promising technology due to its high efficiency and compatibility with renewable energy sources. However, dynamic operating conditions and intermittent renewable input accelerate electrolyzer degradation, reducing reliability and system lifespan. Predictive maintenance (PdM), supported by artificial intelligence (AI), offers a data-driven approach to anticipate failures and improve operational durability. This review systematically investigates AI-based PdM approaches for electrolyzers, with an emphasis on long short-term memory (LSTM) networks and Internet of things (IoT) integration. Following PRISMA 2020 guidelines, 35 …

Dynamic Focal Loss Adjustment For Railway Defect Detection, Mehmet Koç, Ridvan Özdemi̇r, Ömer Gerek

Turkish Journal of Electrical Engineering and Computer Sciences

Railway infrastructure is critical to the safe and efficient operation of transportation systems, and the early detection of defects is essential for preventing catastrophic failures. Automated defect detection methods are therefore crucial for maintaining continuous safety while reducing maintenance costs. Although Focal Loss is widely used in object detection under class-imbalanced conditions, its fixed α parameter may limit its effectiveness in detecting rare defects. In this study, we propose an adaptive α-tuned Focal Loss approach that dynamically adjusts class weights based on average precision (AP) values. By iteratively optimizing α without relying on gradient-based optimization, the proposed method improves the …

Relative Rate Observer-Based Online Tuning Mechanism For Single-Input Interval Type-2 Fuzzy Pid Controllers, Oqba Aldreiei, Cenk Ulu, Mert Can Kurucu, Müjde Güzelkaya

Turkish Journal of Electrical Engineering and Computer Sciences

The characteristics of the footprint of uncertainty (FOU) in interval type-2 membership functions (IT2-MFs) are crucial to the performance and robustness of interval type-2 fuzzy controllers (IT2-FCs). However, existing IT2-FC design approaches mostly use fixed FOU structures. This study proposes an online membership function (MF) adjustment mechanism for a single-input interval type-2 fuzzy PID controller (SIT2-FPID)  that adjusts the FOU of the antecedent MFs and weights of the consequent MFs, respectively, to achieve high performance and robustness. The proposed online adjustment mechanism consists of a relative rate observer (RRO), a two-input rule-base adjustment system, and a first-order smoothing filter. The …

Cuip-X25: A Real-World Network Intrusion Dataset For Next-Generation Ai-Driven Security, Arshad Iqbal, Sohail Asghar

Turkish Journal of Electrical Engineering and Computer Sciences

The efficacy of artificial intelligence (AI) in intrusion detection systems (IDS) is critically dependent on high-fidelity training data. However, as detailed in the manuscript's literature review, existing benchmark datasets are predominantly synthetic, outdated, or imbalanced and fail to capture the complexity of the contemporary threat landscape. To bridge this gap, this study introduces CUIP-X25, a novel real-world cyber-attack dataset captured over a four-month period using a dionaea honeypot deployed on a public network. Unlike synthetic alternatives, this dataset provides an authentic representation of modern adversarial tactics, techniques, and procedures, encompassing 3.16 million real events across ten distinct attack categories, including …

Robust Load Frequency Control For Multiarea Electrical Power Systems Via Analytical Proportional-Integral-Derivative Plus Second Order Derivative Controller Design, Yavuz Güler, Mustafa Nalbantoğlu, Ibrahim Kaya

Turkish Journal of Electrical Engineering and Computer Sciences

This research presents a proportional-integral-derivative plus second order derivative (PIDD2) controller design based on the Direct Synthesis Method (DSM) for load frequency control (LFC) of interconnected power systems. The parameters of the proposed PIDD2 controller are determined using the DSM, which offers an analytical approach for tuning. The design approaches have been developed specifically for single, two, and three-area power systems, encompassing nonreheated and reheated thermal turbines. In the proposed design method, the best values of PIDD2 controller parameters were found by using a multicriteria objective function that includes the integral of absolute error (IAE) and settling time. In response …

Boundary Layer Sliding Mode Control Strategy For Variable-Speed Compressor In Deep Freezers: Experimental Validation Of Energy Efficiency And Freezing Capacity, Sertan Aksoy, Kami̇l Çeti̇n, Sezai̇ Taşkin

Turkish Journal of Electrical Engineering and Computer Sciences

This study presents the design and experimental validation of a nonlinear sliding mode controller developed for a deep freezer equipped with a variable-speed compressor. The proposed control strategy aims to minimize energy consumption while maintaining rapid and stable cooling performance under varying ambient conditions. A detailed thermal model of the deep freezer was established using an equivalent resistance–capacitance network representation, enabling precise analysis of temperature dynamics. The sliding mode-based control algorithm dynamically adjusts the compressor’s operating frequency according to temperature deviation, ambient conditions, and time-dependent factors, providing robust performance without requiring parameter retuning for different models. Beyond theoretical-based analysis, a …

Impact Of Physical Disabilities On Daily Life, Mobility, And Public Health Outcomes Among Internally Displaced Children In Nigeria, Winnifred Obeya-Ekoja

Walden Dissertations and Doctoral Studies

The growing population of internally displaced persons (IDPs) in Nigeria presents significant public health challenges for children with physical disabilities. This study investigated how physical disabilities affect daily life, mobility, access to resources, and health outcomes among internally displaced children in IDP camps in Benue State, Nigeria. Guided by the ecological model of health behavior, the study examined caregivers’ experiences of children’s self-care, daily activities, environmental and interpersonal conditions, sanitation, and access to healthcare. A basic qualitative design used semi-structured interviews with parents and caregivers selected through purposive and snowball sampling. Data were analyzed using Braun and Clarke’s six-phase thematic …

Spartan Daily, September 16, 2026, San Jose State University, School Of Journalism And Mass Communications

Spartan Daily, 2026

Volume 167, Issue 11

Empowering Edge Intelligence Through Reparameterized Lightweight Transformers And Distributed Inference, Hosein Esmaeili, Mohammad Ali Afshar Kazemi, Reza Radfar, Nazanin Pilevari

Turkish Journal of Electrical Engineering and Computer Sciences

Deploying advanced transformer-based models on resource-constrained edge devices remains a significant challenge due to their high memory footprint and substantial compute requirements. In this paper, we propose a reparameterized transformer framework that integrates High-Rank Factorization (HRF) during training, layer merging at inference, and dynamic, load-balanced distributed inference across multiple devices. To further reduce resource usage, our framework supports mixed-precision quantization down to 4-bit, enabling flexible accuracy–latency–energy trade-offs. Experimental evaluations on the ESC-50 environmental sound dataset demonstrate that our method matches or exceeds the performance of larger baseline models while using 20–30% fewer parameters, achieving up to 48% latency reduction in …

Developing A Protocol To Obtain Source Directivity Of Hydroacoustic Transducers In A Water Tank, Benjamin White

Undergraduate Honors Theses

This thesis describes the formulation and application of a methodology designed to obtain source directivity of hydroacoustic transducers in the BYU Underwater Acoustics Laboratory. Piezoelectric transducers are presented, and common methodologies to measure their directivity are reviewed. The schematics of the BYU Underwater Acoustics Lab are explained, including the use of positioning robots to position the source-receiver pair in the measurement chain. The protocol is divided into different configurations comprising various source-receiver orientations. The processes of time gating, calculation of OASPL, and plotting onto directional axes are described. The protocol is tested across four different alternative configurations, including one method …

Common Ground Newsletter Fall 2026, Missouri University Of Science And Technology

Common Ground

- Q&A Experiences

- Shaping the next generation

- Chi Epsilon earns four awards

- Summer Camps

- Design Team Results

Measurement-Aware Zero-Phase Iterative Learning Control For Robust Regulation Of Nonideal Boost Converters In Electric Vehicle Fast Charging, Aytaç Altan, Mohammed S. Alzaidi, Cağfer Yanarateş

Turkish Journal of Electrical Engineering and Computer Sciences

Integrating battery energy storage with DC-DC boost converters for electric vehicle fast charging exposes the regulator to ageing-induced parameter drift, periodic load pulses, and, critically, the nonidealities in the output-voltage sensing chain. This paper proposes a measurement-aware, zero-phase iterative learning control scheme for robust output-voltage regulation of a nonideal boost converter whose parameters are matched to those of a commercial Texas Instruments TPS6102x battery regulator. The controller combines an inner proportional-integral stabilizing loop with an outer zero-phase learning law that updates a feedforward correction based on the sensor-captured output trajectory; a forward-backward robustness filter suppresses the amplification of measurement noise …

Degree Assortativity And Estimation Of Degree Distribution In A Contact Network Of People Who Inject Drugs, Peter Geissert

Dissertations and Theses

This dissertation analyzes data from a respondent driven sampling (RDS) study of people who inject drugs in Portland, OR.  The objective was to assess assumptions for the use of weighted estimators to estimate a population physical contact (syringe sharing) network degree distribution.

Visualization of degree distribution for social and physical networks, Kolmogorov-Smirnov tests of difference, and kernel tests of equivalence were used for comparison of distributions. Spearman's rho and GAM non-parametric regression models were used to test for association and assess non-monotonic relationship. The validity of Markov chain assumptions for RDS was assessed using a transition matrix, Markov chain graphs, …

Kenilworth Holdings Llc V. New York City Rent Guidelines Board

All Decisions

Multiple landlord LLCs bring this Article 78 / declaratory judgment action challenging RGB Apartment and Loft Order No. 58 (June 25, 2026), the Board's first rent freeze since its 1969 inception, covering all rent-stabilized apartments for leases commencing October 1, 2026 through September 30, 2027. Petitioners allege the freeze was a predetermined outcome engineered by the mayor's Board appointments and campaign promises, pointing to a Board member who resigned the morning of the vote citing procedural irregularities; they seek annulment of the order and expedited discovery of communications between the Mayor's Office and the Board. The Board contends the freeze …

Cover And Contents

Turkish Journal of Electrical Engineering and Computer Sciences

No abstract provided.

A Binary Multiobjective Hippopotamus Optimization Algorithm For Feature Selection In Phishing Website Detection, Fatima Belmessaoud, Sofiane Maza, Djaafar Zouache

Turkish Journal of Electrical Engineering and Computer Sciences

Phishing website detection remains a major challenge in cybersecurity as attackers continuously develop new techniques to deceive users. Identifying the most informative features from large datasets is essential to improve classification accuracy while reducing computational complexity. Feature selection is therefore widely addressed using metaheuristic optimization techniques due to their flexibility and global search capability. In this study, we propose a Binary Multiobjective Hippopotamus Optimization Algorithm (B-MOHOA) for feature selection in phishing website detection. The proposed method simultaneously optimizes two conflicting objectives: maximizing classification accuracy and minimizing the number of selected features. Unlike many existing studies that mainly focus on transfer …