Digital Commons Network^™

Construction And Application Of Clinical Evidence Framework For Brain-Computer Interface, Wenxiu Qi, Cheng Zhou

Bulletin of Chinese Academy of Sciences (Chinese Version)

Brain-computer interface systems are emerging neurotechnologies that are gradually moving from laboratory research toward clinical application. However, their inherent features, including small sample sizes, heterogeneous technical pathways, and rapid product iteration, make it difficult to integrate safety and efficacy data across studies or to conduct meaningful cross-study comparisons. These challenges not only hinder the cumulative development of evidence in evidence-based medicine, but also complicate the assessment of clinical access and regulatory review. In addition, subjective evidence, such as patient experience, remains insufficiently captured in existing evaluation frameworks. It is therefore necessary to examine the structure of evidence for brain-computer interface …

On-Device Computing Systems For Embodied Ai: Current Research Status And Strategic Directions, Shaoshan Liu, Zhenhua Zhu, Yiming Gan, Yu Wang, Yuan Xie

Bulletin of Chinese Academy of Sciences (Chinese Version)

Embodied AI is emerging as a key paradigm empowering general-purpose autonomy, but it requires on-device computing systems that simultaneously support high-throughput “cognition–planning” tasks and millisecond-level real-time “perception–control” loops. Converging solutions now coalesce around three pillars: (1) dataflow- and chiplet-based architectures, (2) memory-centric heterogeneous dies, and (3) RISC-V customizable cores with open tool-chains. This study distills the latest technical progress, pinpoints the remaining core technical bottlenecks, and charts an actionable course for academia, industry, and policymakers. The study calls for unified benchmarking and standardization, open-source software–hardware ecosystems, memory-centric dataflow architectures, and efficient on-device deployment of embodied foundation models. Finally, it outlines …

Nightside Electron Precipitation Patterns As Observed By Elfin And Cirbe Cubesats, Kun Zhang, Anton V. Artemyev, Xinlin Li, Xiao-Jia Zhang, Vassilis Angelopoulos, Yang Mei, Zheng Xiang, Niklas Grimmich

Publications

The rapidly expanding fleet of low-altitude CubeSats equipped with energetic particle detectors brings new opportunities for monitoring the dynamics of the radiation belt and near-Earth plasma sheet. Despite their small sizes, CubeSats can carry state-of-the-art instruments that provide electron flux measurements with finer energy resolution and broader energy coverage, compared to conventional missions such as POES satellites. The recently launched CIRBE CubeSat measures 250–6,000 keV electrons with extremely high energy resolution, however, CIRBE typically only measures locally-trapped electrons and cannot directly measure the precipitating electrons. This work aims to develop a technique for identifying indications of nightside precipitation using the …

Selective Citation: The Systematic Omission Of Established Regional Literature, İrem Eli̇tez

Turkish Journal of Earth Sciences

No abstract provided.

Integrated Assessment Of Groundwater Quality And Human Health Risks In A Semiarid Region Of Kemaliye (Türkiye), Veli̇ Keski̇n, Celaletti̇n Şi̇mşek

Turkish Journal of Earth Sciences

In this study, the hydrochemical characteristics, drinking water suitability, and potential human health risks of groundwater in the Karapınar region (Kemaliye, Erzincan, Türkiye), which has become a critical drinking water resource due to drought associated with climate change and the depletion of surface water resources, were investigated using an integrated multiparameter approach. Within the scope of the study, a total of 18 water samples, comprising 13 spring water samples and 5 groundwater samples obtained from wells, were collected during the dry season (October 2021) and analyzed for major ions, physicochemical parameters, nitrate, and trace elements. The suitability of the samples …

Signals In The Ionosphere Ahead Of Tsunami Arrival, Svetlana Riabova, Sergey Shalimov

Turkish Journal of Earth Sciences

We consider the impact of the tsunami propagating after the earthquake in Tohoku on the ionosphere according to measurements from the Hawaiian Islands, i.e., at a fairly large distance from the epicenter of the earthquake. These measurements, taken at a tidal tsunami monitoring station, at a magnetometric station, and by GPS, were used to record the arrival of the tsunami. We experimentally establish that the arrival of atmospheric waves generated by the tsunami significantly advanced the arrival of sea waves at the observation point, and this advance from one source was recorded in both the lower and upper ionosphere. Attention …

Editorial Note To The Article “Identification Of A Previously Unrecognized Listric Fault Beneath The Acıpayam Graben: Insights From Integrated Dinsar And Field Observations” [Turkish Journal Of Earth Sciences 35 (1) 2026 20-41], Orhan Tatar

Turkish Journal of Earth Sciences

No abstract provided.

Possible Fluid Contributions From Active Faults To Mercury Distribution In Surface Sediments Of The Gemlik Gulf And Health Risk Assessment, Erol Sari, M. Namik Çağatay, Tuğçe Nagi̇han Arslan Kaya, Zeynep Çeti̇n, Nuray Çağlar

Turkish Journal of Earth Sciences

The Gemlik Gulf, located in the eastern part of the Sea of Marmara (Türkiye), is recognized as a relatively contaminated marine environment, influenced by a variety of natural and anthropogenic inputs. A comprehensive geochemical study was performed to examine the distribution of total mercury (THg) in surface sediments and to elucidate the possible sources contributing to its accumulation. The analysis revealed that THg concentrations ranged from 485 to 6486 ng/g, with all measured values substantially exceeding the average shale background concentration of 400 ng/g, indicating significant enrichment. According to sediment quality guidelines, none of the samples exceeded the effects range …

Paleoecology Of Loftusia Species (Large Benthic Foraminifera) In The Zagros Basin, North Of The Neotethys, Hossein Ghanbarloo, Amrollah Safari

Turkish Journal of Earth Sciences

Paleoecological analyses based on the wall structure of the genus Loftusia were carried out in the Maastrichtian deposits of seven outcrops of the Zagros Basin. Two types of particles are present within the wall structure: (1) tiny fossil grains and (2) detrital grains. Tiny fossil grains consist of smaller foraminifera and other small microorganism tests. Foraminiferal tests are associated with miliolid, textulariid, and rotaliid forms. Detrital grains include intraclasts and extraclasts. The presence of different particles in the test wall of this genus and the abundance of this genus in nutrient-rich conditions indicate that Loftusia are probably opportunistic foraminifera. This …

Neoproterozoic Uranium-Mineralized Sedimentary Rocks From The Kaladgi Basin, Dharwar Craton, Southwestern India: Source And Transport Mechanism Of Uranium, Ponnalagu Govindaraj, Arumugam Shanmugasundaram, Sooriamuthu Ramasamy, Muthusamy Ravichandran

Turkish Journal of Earth Sciences

The Kaladgi Basin of the Dharwar Craton, southeast India, hosts Proterozoic unconformity-related uranium (U) mineralization controlled by faulted contacts between Archean basement and Proterozoic cover sediments. To understand the ore-forming processes, 25 core samples from the Cave Temple Arenite were analyzed using whole-rock geochemistry and fluid inclusion microthermometry. U concentrations reach up to 0.13% U3O8 in the basal arenite and lower conglomerate, whereas the basement schist records only 0.0017% U. Whole-rock data reveal high SiO2 contents (72–97 wt.%), variable Al2O3 (0.4–12.9 wt.%), and enrichments in U (0.38–6.63 ppm), Th (1.5–13.7 ppm), and trace elements such as Cu, Pb, and Ni …

Citation Scope And Scientific Relevance In An Event-Based Seismotectonic Study: Reply To The Comment By Elitez On Eski (2026), Semi̇h Eski̇

Turkish Journal of Earth Sciences

No abstract provided.

Protocol For Integrating Vessel Networks And Environmental Matching To Inform Cost-Effective Archipelago Biosecurity Planning And Management, Chi T.U. Le, Chad L. Hewitt, Marnie L. Campbell

Research outputs 2022 to 2026

Inter-island vessel networks support economic activity but also enable secondary spread of non-native species. By integrating vessel-movement data, network analysis, and environmental matching, we present a protocol for generating a cost-effective biosecurity decision-support tool by assessing both the relative economic importance and the relative risks of species spread within a vessel traffic system. We outline steps for data curation, network construction, and sea surface temperature-based environmental similarity calculation. We then detail procedures for the translation of outputs into management recommendations. For complete details on the use and execution of this protocol, please refer to Campbell et al. ¹

Statistical Triangulation: Weighing Multiple Statistical Tools In Macro-Level Housing Research, Julio Montanez, Amy Donley, Jacquelyn Reiss

Journal of Applied Disciplines

Homelessness and housing research has a detection problem, in which understanding housing issues (e.g., substandard housing) is plagued by problems like undercounting and incomplete data. To partially compensate for these pitfalls, the current research engages in an exercise aiming to sharpen the statistical approach to homelessness and housing research. The macro-level sample included Florida’s 27 Continuums of Care geographies (composed of one or more Florida counties). The dependent variables were sheltered homelessness, energy-based substandard housing, and plumbing-based substandard housing. The independent variables were misdemeanor partner violence rates, felony partner violence rates, high school non-completion rates, urbanicity, and population burdens of …

The Fossil Pearls Of The Million-Pearls Flowstone, Fairgrounds Room, Fort Stanton Cave, New Mexico Usa, Victor J. Polyak, Paula P. Provencio, Yemane Asmerom

International Journal of Speleology

‘Fossil’ cave pearls in the Fairgrounds Room of Fort Stanton Cave form two distinct layers in a flowstone sample, FS-14-2. The flowstone in the Fairgrounds Room covers a mud-silt bank and the extinct streambed that extends across the room. Uranium-series dates of two pieces of flowstone from this room, one piece from the higher end of the flowstone (FS-14-1, devoid of pearls), and another piece from the lower end of the flowstone (FS-14-2, rich in pearls), show that the flowstone was deposited during the Last Glacial period (60,000 to 11,000 yr BP).  The two cave-pearl layers in FS-14-2 yielded U-series …

Data-Driven Risk Mapping For Safer Roads: Unincorporated Dekalb County, Georgia, Getachew B. Demisse, Stacy C. Grear, Araya D. Araya, Shimelis Gebru, Solomon Negash, Leo Ladefian, Carlo Frate

The Geographical Bulletin

This study presents a decade-long spatiotemporal analysis of more than 206,000 traffic accidents recorded between 2015 and 2024 in unincorporated DeKalb County, Georgia. The primary goal of the study is to identify critical patterns of roadway risk and inform data‑driven safety interventions. Using crash records from the Georgia Department of Transportation (GDOT) AASHTOWare Safety platform and standardized crash‑rate calculations, the analysis revealed strong temporal regularities, including elevated crash frequencies during afternoon peak hours, Fridays, and seasonal transition periods such as October. Spatial analyses further demonstrate that crashes are highly concentrated along a limited subset of corridors, consistent with High Injury …

A Calibrated And Conformal Deep Learning Framework For Trustworthy Antinuclear Antibody Pattern Recognition With Selective Referral To Experts, Hussein Ali Hussein Al Naffakh, Ahmed Dheyaa Radhi, Raghdah Maytham Hameed, Muntaha Abdullah Reishaan, Fouad A. Majeed, Rozaida Ghazali

Karbala International Journal of Modern Science

Reading antinuclear antibody patterns on human epithelial cells by indirect immunofluorescence is the reference screen for systemic autoimmune rheumatic diseases, but it is slow, subjective, and variable between observers. Deep learning reaches high accuracy on this task, yet most systems return a single prediction without stating how reliable it is, which is unsafe in a diagnostic workflow. This paper presents an intelligent decision support framework built around a single calibrated uncertainty signal. That signal is the control variable for four reliability modules: confidence calibration, conformal prediction, error detection, and selective referral. A feature space out of distribution detector serves as …

Collaborative Research: Influence Of Fault Frictional Healing And Realistic Tectonic Loading Rates On Shallow Subduction Megathrust Locking, Srisharan Shreedharan

Funded Research Records

No abstract provided.

Photochemistry At The Air-Aerosol Interface, Yi Rao

Funded Research Records

No abstract provided.

Exceptional Holography (2025 Renewal, Revised Budget), Oscar Varela

Funded Research Records

No abstract provided.

Resilient Ethical Governance By Design: Building Resilience For Future-Ready Smart Cities Against Emerging Technology Disruptions In Public Sector – A Case Study Of Dallas Smart City, Emmanuel Asamoah Asare

Doctoral Dissertations and Projects

This dissertation examines how Dallas’s smart city strategic policies foster resilience against disruptions associated with emerging technologies, particularly artificial intelligence and Internet of Things systems. Using a convergent mixed-methods comparative case study, Dallas serves as the primary case, Austin serves as a U.S. municipal comparator, and Barcelona serves as a qualitative benchmark for ethical and trust-centered smart city governance. The study integrates document analysis, broadband and digital equity indicators, stakeholder engagement evidence, and exploratory quantitative comparisons to assess how governance adaptability, preparedness, functionality, equity, and stakeholder trust shape resilience outcomes.

The findings provide partial support for the study’s hypotheses. Dallas …

Comparison Of Gravity Separation And Flotation For Pyrite Recovery From Tailings, Gülay Bulut, Gönül Göksu Gökçe, Dilruba Karamanlı, Oğuzhan Mert Gürkan, Ergin Sarp Zenzirci, Binnur Kırım, Alim Gül

Journal of Sustainable Mining

Tailings generated during the production of lead, zinc, and copper concentrates contain significant amounts of sulfide minerals, particularly pyrite. Pyrite, which remains in tailings after the recovery of other metals, is one of the main contributors to acid mine drainage (AMD). Therefore, recovering pyrite from tailings is environmentally and economically an important issue. In this study, pyrite recovery from tailings was investigated using flotation and gravity separation methods. Mineralogical characterization and liberation analyses were conducted by Mineral Liberation Analysis (MLA), indicating that pyrite is the major sulfide mineral with over 76% liberation degree even in the coarsest fractions. Flotation tests …

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 …

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 …

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 …

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 …