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Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications, Yifang Wang, Yuan He, Yao Huang, Wanbing He, Yi Jiao, Congqiao Li, Ke Li, Beijiang Liu, Yingqi Ma, Yugang Ma, Longgang Pang, Fazhi Qi, Sichao Tan, Chunpeng Wang, Meng Wang, Xiaoheng Xu, Xing Xu, Zhentang Zhao, Yingxun Zhang, Zhengde Zhang, Hongwei Zhao, Lina Zhao Jun 2026

Artificial Intelligence Empowers Particle Physics And Nuclear Physics: From Fundamental Research To Major Applications, Yifang Wang, Yuan He, Yao Huang, Wanbing He, Yi Jiao, Congqiao Li, Ke Li, Beijiang Liu, Yingqi Ma, Yugang Ma, Longgang Pang, Fazhi Qi, Sichao Tan, Chunpeng Wang, Meng Wang, Xiaoheng Xu, Xing Xu, Zhentang Zhao, Yingxun Zhang, Zhengde Zhang, Hongwei Zhao, Lina Zhao

Bulletin of Chinese Academy of Sciences (Chinese Version)

Particle physics and nuclear physics are core foundational disciplines for exploring the fundamental structure of matter and the origin of the universe. The deep integration of artificial intelligence (AI) technology is providing entirely new pathways to address systemic challenges such as the processing of massive amounts of multimodal data, the realization of extreme experimental conditions, bottlenecks in theoretical calculations, and the intelligent control of large-scale scientific facilities. The article systematically elaborates on how AI deeply empowers particle physics and nuclear physics, particularly in major application scenarios such as research on the fundamental structure and origin of mass of matter, the …

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Artificial Intelligence Empowered Biological Research: Paradigm Shifts, Application Scenarios, And Strategic Layout, Xinguang Zhu, Yiming Bao, Zhenong Jin, Xin Li, Sijia Wang, Yueming Wang, Yungui Yang, Cao Xu, Yan Xiong, Bin Han Jun 2026

Artificial Intelligence Empowered Biological Research: Paradigm Shifts, Application Scenarios, And Strategic Layout, Xinguang Zhu, Yiming Bao, Zhenong Jin, Xin Li, Sijia Wang, Yueming Wang, Yungui Yang, Cao Xu, Yan Xiong, Bin Han

Bulletin of Chinese Academy of Sciences (Chinese Version)

Life related processes are characterized by high dimensionality and multi-scale properties. Understanding mechanisms underpinning life processes helps promote national healthcare, agricultural development, sustainable ecological civilization, and national security. Current life science research is confronted with an enormous challenge of dimensionality stemming from data explosion and data fragmentation, for which the recent rapid advancement of artificial intelligence (AI) provides novel solutions. AI will catalyze a paradigm shift in life science research from the current experiment based empirical induction to a new closed-loop knowledge acquisition including large scale data collection, model building, model prediction, experimental validation, and iterative of these procedures. Life …

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Artificial Intelligence–Driven Paradigm Transformation In Biopharmaceutical R&D: Applications And Emerging Scenarios, Lili Liu, Mingyue Zheng, Ye Yuan, Xutong Li, Rong Fan, Wei Wei, Jinxin Zhao, Guobin Qi, Hua Yue, Likun Gong, Songping Zhang, Jiachen Li, Yuchen Sun, Xiaoyan Chen, Yao Chen, Xin Liu, Xiao Zhang, Yuehong Gao, Jianfeng Li, Kaixian Chen, Guanghui Ma, Jianmin Yue Jun 2026

Artificial Intelligence–Driven Paradigm Transformation In Biopharmaceutical R&D: Applications And Emerging Scenarios, Lili Liu, Mingyue Zheng, Ye Yuan, Xutong Li, Rong Fan, Wei Wei, Jinxin Zhao, Guobin Qi, Hua Yue, Likun Gong, Songping Zhang, Jiachen Li, Yuchen Sun, Xiaoyan Chen, Yao Chen, Xin Liu, Xiao Zhang, Yuehong Gao, Jianfeng Li, Kaixian Chen, Guanghui Ma, Jianmin Yue

Bulletin of Chinese Academy of Sciences (Chinese Version)

The biopharmaceutical industry is a critical domain underpinning national scientific and technological innovation development and public health. With the rapid advancement of artificial intelligence (AI) and its deep integration with the life sciences, biomedicine research is undergoing a paradigm shift from traditional experience-driven trial-and-error approaches to data-driven and predictive validation-based models. This study systematically examines the pathways for reshaping research in biomedicine paradigms under the convergence of data-driven, mechanism-driven, and intelligence-driven approaches. It focuses on recent advances in the application of AI across key stages, including drug discovery and design, druggability evaluation, delivery system design and optimization, nonclinical and clinical …

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Artificial Intelligence For Cybersecurity: Opportunities, Challenges, And Approaches, Kai Chen, Ding Li, Guozhu Meng, Shouling Ji, Changjiang Li, Yi Yang, Dengguo Feng Jun 2026

Artificial Intelligence For Cybersecurity: Opportunities, Challenges, And Approaches, Kai Chen, Ding Li, Guozhu Meng, Shouling Ji, Changjiang Li, Yi Yang, Dengguo Feng

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cybersecurity research, institutional structures, and governance policies are undergoing profound transformations. Currently, increasingly covert and rapidly evolving intelligent attacks, coupled with the national urgent expectations for high-level security, are driving significant shifts in the roles and interactions of governments, research institutions, and enterprises. Consequently, this study, based on analyzing the challenges and opportunities of the AI era, explores core application scenarios such as critical information infrastructure protection, national data security, and the maintenance of cyberspace sovereignty. It provides an analysis of artificial intelligence in dimensions such as correlation and causality, and proposes a governance framework, aiming to provide insights for …

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Artificial Intelligence For Astronomy: Strategic Opportunities, Policy Challenges And Development Strategies, Jin Chang, Yihan Song, Bing Du, Kefei Wu, Ali Luo, Jifeng Liu Jun 2026

Artificial Intelligence For Astronomy: Strategic Opportunities, Policy Challenges And Development Strategies, Jin Chang, Yihan Song, Bing Du, Kefei Wu, Ali Luo, Jifeng Liu

Bulletin of Chinese Academy of Sciences (Chinese Version)

To alleviate the bottlenecks hindering the integrated development of artificial intelligence and astronomy in China and to reinforce the country’s strategic edge in science and technology, this study uses systematic analysis and path-comparison approaches to examine the policy requirements for their deep integration. The findings indicate that this topic is closely tied to global competition in science and technology, strategic security, and industrial upgrading. At present, the world has entered a new “astronomy + AI” paradigm, with the United States and the European Union already having taken the lead in establishing corresponding strategic frameworks. Leveraging major scientific infrastructures such as …

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Artificial Intelligence Empowering Remote Sensing: Challenges, Paradigms And Strategic Layout, Jiayuan Shen, Peirui Cheng, Zhirui Wang, Wei Liang, Xian Sun, Yirong Wu Jun 2026

Artificial Intelligence Empowering Remote Sensing: Challenges, Paradigms And Strategic Layout, Jiayuan Shen, Peirui Cheng, Zhirui Wang, Wei Liang, Xian Sun, Yirong Wu

Bulletin of Chinese Academy of Sciences (Chinese Version)

Remote sensing science and technology, as a key discipline for Earth observation and global change research, faces systemic challenges in processing massive multi-source data, accurately extracting complex information, and delivering high-timeliness application services. The rapid advances in artificial intelligence (AI) provide a new opportunity to address the deep-seated dilemma in remote sensing of being “data-rich but insufficient in effective information mining”. Guided by a problem-oriented approach, this study first systematically analyzes the core challenges facing the development of remote sensing across four dimensions: data understanding, technical methods, scientific mechanisms, and application ecosystems. It then reviews the technical evolution of AI-empowered …

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Artificial Intelligence For Deep Earth Science: Key Challenges, Major Application Scenarios And Development Pathways, Qingyun Di, Liang Zhao, Yikang Zheng, Zhi Geng, Zhichao Yu, Xiaocai Shan, Chao Li, Zhiyao Xu, Pengfei Lv Jun 2026

Artificial Intelligence For Deep Earth Science: Key Challenges, Major Application Scenarios And Development Pathways, Qingyun Di, Liang Zhao, Yikang Zheng, Zhi Geng, Zhichao Yu, Xiaocai Shan, Chao Li, Zhiyao Xu, Pengfei Lv

Bulletin of Chinese Academy of Sciences (Chinese Version)

Deep Earth science is central to understanding Earth’s internal architecture and the coupled evolution of its major spheres, while also underpinning energy security, the supply of critical mineral resources, and resilience to major geohazards. Nevertheless, the advancement of deep Earth science is currently hindered by insufficient in situ observations under extreme conditions, the difficulty of integrating multi-source heterogeneous data, and the limited capability to model complex multiphysics coupling processes. Recent advances in artificial intelligence offer a potential route beyond these limitations. By integrating data-driven learning with physical and geological understanding, AI is reshaping deep Earth science from empirical interpretation to …

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Relay Selection And User Scheduling In Reconfigurable Intelligent Surface Assisted Millimeter-Wave D2d Communication, Lakshmikanta Sau Jun 2026

Relay Selection And User Scheduling In Reconfigurable Intelligent Surface Assisted Millimeter-Wave D2d Communication, Lakshmikanta Sau

Doctoral Theses

Reconfigurable intelligent surface (RIS) assisted millimeter wave (mmWave) device to device (D2D) communication has recently been proposed as a viable solution to support the overwhelming data traffic in fifth-generation (5G) and beyond wireless networks. However, due to the substantial propagation and penetration losses of mmWave, a direct line of sight (LoS) link between a pair of proximity devices is required for effective communication. Static obstacles like trees and buildings can easily obstruct the direct LoS connectivity between a device pair. In such cases, RISs help to establish an indirect LoS link between an obstructed device pair by reflecting the signals …

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The Ecotoxicological Implications Of Switching From Fluorescent To Light Emitting Diode Lighting For Zooplankton Culturing And Whole Effluent Toxicity Testing, Orithea Z. Regn Jun 2026

The Ecotoxicological Implications Of Switching From Fluorescent To Light Emitting Diode Lighting For Zooplankton Culturing And Whole Effluent Toxicity Testing, Orithea Z. Regn

Student Theses and Dissertations

In the global transition toward light emitting diode (LED) lighting, an understudied area is the impact on the culturing and testing of Whole Effluent Toxicity (WET) testing organisms, more specifically, the zooplankton species. Without comparison to the current lighting used for culturing and testing, it is unknown if there will be an impact on performance, which could affect effluent, regulatory, and product safety decisions. This dissertation investigated if culturing and reference toxicity testing using sodium chloride for Ceriodaphnia dubia, Daphnia magna, and D. pulex under LED lighting was comparable to fluorescent. Comparisons were made between two laboratories and by season, …

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American Sign Language Recognition And Analysis Using Deep Learning, Saurabh Kumar Soni Jun 2026

American Sign Language Recognition And Analysis Using Deep Learning, Saurabh Kumar Soni

Master’s Dissertations

In this work I build a system that recognizes isolated American Sign Language (ASL) words, and I use it to ask one fairly direct question: when training data is scarce, is it better to look at the video pixels or at the geometry of the signer’s body? To find out, I train two very different models on exactly the same clips. The first is appearance-based. Every frame is run through standard preprocessing and a ResNet50 backbone pre-trained on ImageNet, which turns it into a 2048-dimensional feature vector, and a Bidirectional LSTM then reads that sequence over time. The second model …

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Trophic Structure Of Reef-Fish Assemblages In The Eastern Gulf Of Mexico Varies By Depth And Reef Type, Jessica L. Van Vaerenbergh Jun 2026

Trophic Structure Of Reef-Fish Assemblages In The Eastern Gulf Of Mexico Varies By Depth And Reef Type, Jessica L. Van Vaerenbergh

USF Tampa Graduate Theses and Dissertations

Globally, marine ecosystems are increasingly threatened by anthropogenic stressors, leading to reef degradation, changes in reef-fish assemblages, and altered trophic structure. In this study, I investigated reef-fish underwater visual survey data collected over a decade (2013-2023) from paired natural and artificial reefs in the eastern Gulf of Mexico. I applied the novel Normalized Reef Status Index (NRSI) to evaluate how biomass was distributed across the three trophic categories (i.e., Lower Trophic Position (LTP; 2.0-2.9), Central Trophic Position (CTP; 3.0-3.9), and Upper Trophic Position (UTP; ≥4.0). This index is a metric to assess the ecological status of reef systems by investigating …

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Learnable Structured Attention For Student-Aware Knowledge Distillation In Dense Prediction, Chen Liu Jun 2026

Learnable Structured Attention For Student-Aware Knowledge Distillation In Dense Prediction, Chen Liu

ETDs from 2020-2029

Dense prediction tasks, including object detection and semantic segmentation, require models to produce structured predictions and are widely used in real-world vision applications. Although deep networks have achieved strong performance on these tasks, their high computational cost limits deployment on resource-constrained systems such as autonomous-driving vehicles. Knowledge distillation (KD) addresses this issue by transferring knowledge from a large teacher model to a compact student model. However, existing distillation methods for dense prediction face greater challenges than those for classification due to the more complex task requirements. To overcome the challenges, this thesis presents a unified study of adaptive distillation for …

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Production, Purification, And Crystallization Of The Recombinant Her2 Tyrosine Kinase Domain (Her2-Tkd), Edanur Topalan, Hali̇li̇brahi̇m Çi̇ftçi̇, Hasan Demi̇rci̇ Jun 2026

Production, Purification, And Crystallization Of The Recombinant Her2 Tyrosine Kinase Domain (Her2-Tkd), Edanur Topalan, Hali̇li̇brahi̇m Çi̇ftçi̇, Hasan Demi̇rci̇

Turkish Journal of Chemistry

The human epidermal growth factor receptor 2 tyrosine kinase domain (HER2-TKD) is an important therapeutic target in oncology. In this study, we developed a practical and cost-effective approach for producing soluble recombinant HER2-TKD in Escherichia coli as a basis for structure-based drug discovery. The gene encoding HER2-TKD was cloned into a pET28a(+) expression vector and expressed in E. coli. Since the protein was initially obtained as inclusion bodies, solubilization with 1.5% sarcosyl was applied to recover it in soluble form. The purified protein was obtained through size-exclusion chromatography, followed by tag removal using reverse affinity purification. Crystallization trials were performed …

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Quantum Engineered Mxene–Graphene–Plasmonic Nanocomposites For Next-Generation Transparent And Flexible Space Photovoltaics, Arash Vaghef-Koodehi Jun 2026

Quantum Engineered Mxene–Graphene–Plasmonic Nanocomposites For Next-Generation Transparent And Flexible Space Photovoltaics, Arash Vaghef-Koodehi

Turkish Journal of Chemistry

This study presents a quantum‑engineered, tricomponent heterostructure comprising Ti3C2T MXene quantum dots (2–5 nm), single‑layer graphene, and plasmonic gold nanoparticles (15 ± 3 nm) uniformly embedded within electrospun polyacrylonitrile nanofibers. This integrated architecture demonstrates a remarkable combination of optical transparency (89.3 ± 1.1%) and power conversion efficiency (19.7 ± 0.4%) under AM0 solar illumination, representing 340% enhancement over state‑of‑the‑art transparent photovoltaic devices. A multiscale computational framework, bridging density functional theory and device‑level drift-diffusion modeling, identifies optimal interlayer spacing (3.4 ± 0.1 Å) as the key to achieving 89.3% charge‑transfer efficiency. Concurrently, localized surface plasmon resonances at 532 nm generate electromagnetic …

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Efficient Heterogeneous Photo-Fenton Degradation Of Azo Dyes Using The Nanocomposite Mgfe2o4/Mos2, Zahra Zeinali, Leila Ershadi Afshar, Naz Chaibakhsh, Farnaz Isapour Jun 2026

Efficient Heterogeneous Photo-Fenton Degradation Of Azo Dyes Using The Nanocomposite Mgfe2o4/Mos2, Zahra Zeinali, Leila Ershadi Afshar, Naz Chaibakhsh, Farnaz Isapour

Turkish Journal of Chemistry

In the present work, a facile hydrothermal route was employed to synthesize the nanocomposite MgFe2O4/MoS2, which acted as a heterogeneous photo-Fenton catalyst for the degradation of a synthetic diazo dye, Acid Blue 113 (AB113). The nanocatalyst produced underwent analysis using multiple characterization techniques. The parameters influencing the oxidative reaction were statistically modeled and optimized using response surface methodology. Optimal degradation efficiency for AB113 (94.92%) was attained at pH 8.79 using 10 mg of MgFe2O4/MoS2 nanocatalyst, 1.6 mL of H2O2, and a reaction duration of 27 min. The synergistic effect resulting from the formation of electron-hole pairs renders the combined photocatalysis …

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Electrochemical Biosensing Of Alpha-Fetoprotein Based On Carboxylated Multi-Walled Nanotube-Polyazur A (In Des)-Gold Nanoparticles, Merve Yilmaz Çilçar, Meli̇ke Bi̇lgi̇ Kamaç Jun 2026

Electrochemical Biosensing Of Alpha-Fetoprotein Based On Carboxylated Multi-Walled Nanotube-Polyazur A (In Des)-Gold Nanoparticles, Merve Yilmaz Çilçar, Meli̇ke Bi̇lgi̇ Kamaç

Turkish Journal of Chemistry

AFP, a cancer biomarker, is monitored during fetal development and in the serum of pregnant women. Sensitive and rapid monitoring of AFP is crucial for effective management. In this study, screen-printed carbon electrodes (SPCEs) modified with multi-walled carbon nanotubes (MWCNT-COOH), polyAzur A (PAA), which was prepared in a deep eutectic solution (DES), and gold nanoparticles (AuNP) were fabricated. AFP biosensors were developed for practical, sensitive, low-cost, and rapid detection of AFP. Optimizations of nanostructures (MWCNT-COOH, AuNP) and polymers (PAADES) were performed. The MWCNT-COOH, PAADES, and AuNP-modified SPCEs were characterized by FE-SEM-EDX, FTIR, and XRD techniques. The amounts of 6-MOH, APTES, …

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[H]-Mediated Enhancement Of The Fenton Reaction Over A Pd/Uio-66(Zr)-F4 Catalyst, Juanhong Li, Suqin Wang, Xin Liu, Feng Liu Jun 2026

[H]-Mediated Enhancement Of The Fenton Reaction Over A Pd/Uio-66(Zr)-F4 Catalyst, Juanhong Li, Suqin Wang, Xin Liu, Feng Liu

Turkish Journal of Chemistry

A [H]-accelerated catalytic Fenton system was developed using Pd/UiO-66(Zr)-F4 as the catalyst. This system enabled the regeneration of Fe²⁺ and facilitated the continuous generation of both ·OH and 1O2 through [H]-mediated electron transfer at ambient temperature and pressure. Under the conditions of 0.2 g L−1 catalyst (Pd loading 0.516 wt%), 25 μM Fe2+, 60 mL min−1 H2 flow (as the [H] source), 20 mM H2O2, and pH 3, approximately 89% of carbamazepine (initial concentration 20 mg L−1) was degraded within 3 h using trace iron. However, the catalytic activity of Pd/UiO-66(Zr)-F4 gradually declined from 89% to 53% over six reaction …

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Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken Jun 2026

Physically Mixed Graphene Aerogel:Carbon Black (Ga:Cb)-Supported Pt Or Hydrothermally Synthesized Ga-Pt/Cb Hybrid Electrocatalysts For Pem Fuel Cells, Emi̇ne Teke Öner, Meli̇s Irmak Aydin, Merve Ni̇da Dursunoğlu, Ayşe Bayrakçeken

Turkish Journal of Chemistry

Graphene aerogels (GAs), having the superior properties of graphene and aerogel structures, are promising support materials for Pt nanoparticles to be used as electrocatalysts for PEM fuel cells. In this study, two routes were followed to synthesize GA-based electrocatalysts. In the first route, after GA synthesis it was physically mixed with carbon black (CB) by changing the mass ratios from 0% to 100% with 25% increments and then decorated with Pt nanoparticles via microwave irradiation, resulting in Pt/GA:CB electrocatalysts. In the second route, firstly, Pt/CB electrocatalyst was synthesized and then GA was hydrothermally added to the Pt/CB by changing the …

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Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo Jun 2026

Modeling And Mitigating Stale Hardcoded Secrets In Version Control History, Katarina Valentine Capalbo

USF Tampa Graduate Theses and Dissertations

Hardcoded secret vulnerabilities remain a growing and persistent problem that can be difficult to mitigate once exposed. While there has been significant research and advancements in identifying and preventing hardcoded secrets, less attention has been given to understanding the risks of leaving these secrets behind in version control history, as well as analyzing the sanitization of hardcoded secrets. These challenges present a growing gap between the risk and ability to mitigate and sanitize existing secret exposures. This thesis begins to address this gap by formalizing a threat model for hardcoded secrets that persist in Git version control history after the …

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Spatial Tax Intelligence: Implementing Integrated Spatial Decision Support Systems For Smart Urban Governance, Wildan R. Irfana, Haldis A. Bahar, Muhammad H. Candra Jun 2026

Spatial Tax Intelligence: Implementing Integrated Spatial Decision Support Systems For Smart Urban Governance, Wildan R. Irfana, Haldis A. Bahar, Muhammad H. Candra

Smart City

The transition toward smart governance requires local governments to adopt data-driven policy approaches, particularly in managing urban tax capacity. However, tax administration in many developing regions remains predominantly tabular and administrative, limiting the ability to capture the spatial dynamics of economic activities. This reveals a critical knowledge gap, as integrated frameworks combining spatial and tax data to identify geographic disparities in tax performance remain limited. Consequently, areas with high economic activity but low tax compliance, referred to as tax blind spots, often remain undetected. This study aims to analyze the effectiveness of integrating spatial and tax data in identifying spatial-tax …

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Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi Jun 2026

Student Worksheets Based On The Local Wisdom Of Besilek Serawai For Sixth-Grade Elementary Science Learning, Mice Agustin, Tomi Hidayat, Irwandi Irwandi

Jurnal Pendidikan Sains

This study aims to develop a Student Worksheet (Lembar Kerja Peserta Didik [LKPD]) based on the local wisdom of Besilek Serawai for sixth-grade elementary science education and to evaluate its validity. The study employed the ADDIE development model, consisting of five stages: Analyze, Design, Develop, Implement, and Evaluate. The developed LKPD integrates Besilek Serawai, a traditional martial art of the Seluma community, with the concept of the human locomotor system in science instruction. The worksheet was validated by two subject-matter experts and two media experts. Material validation yielded an average score of 4.26, equivalent to a validity percentage of 85.2%, …

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You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida Jun 2026

You Mean What? Commognitive Conflict In Resolving Contextual Logarithm Problems, Endrayana Putut Laksminto Emanuel, Fatkul Anam, Radhitya Duta Pradana, Anik Kirana, Sikky El Walida

Jurnal Pendidikan Sains

Students’ approaches to solving contextual mathematics problems involving logarithms vary significantly due to differences in their prior mathematical understanding. These differences may trigger commognitive conflict during the interpretation and reasoning processes when students attempt to construct mathematical meaning from contextual situations. This qualitative study aimed to explore how commognitive conflict emerges as a mechanism of mathematical interpretation in students’ discourse while solving logarithmic contextual problems. Twenty students participated in the study and were grouped based on their performance. One student was selected as the main research subject for an in-depth analysis. The findings reveal that commognitive conflict appeared in two …

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The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani Jun 2026

The Effect Of Project-Based Learning Model On Entrepreneurship (Pjbl-E) With A Deep Learning Approach On Students' Problem-Solving And Cognitive Skills, Ricce Oktasari, Irwandi Irwandi, Siti Darwa Suryani

Jurnal Pendidikan Sains

This study aims to examine the effect of the Entrepreneurship-based Project Based Learning (PjBL-E) model integrated with a pedagogical Deep Learning approach on students’ problem-solving skills and cognitive learning outcomes in biology learning. The novelty of this study lies in the integration of entrepreneurship values and pedagogical deep learning principles into Project Based Learning to create contextual and meaningful learning experiences. Entrepreneurship integration encourages students to develop innovative products, identify real-world problems, and apply biological concepts in practical and socio-economic contexts. Meanwhile, the pedagogical Deep Learning approach promotes reflective thinking, conceptual understanding, critical analysis, and the ability to connect theory …

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Get Ready To Lead: Human-Centered Leadership In An Ai-Driven World, Ellen Ramsey Jun 2026

Get Ready To Lead: Human-Centered Leadership In An Ai-Driven World, Ellen Ramsey

Faculty and Staff Publications & Presentations

As AI becomes increasingly integrated into our daily lives, online students continue to seek instructors who consistently appear, genuinely care about them as individuals, and provide guidance, challenge, and support. AI tools can help with speed and structure, but human-centered leadership keeps connection and meaning at the forefront of the learning experience. 

This interactive workshop invites online instructors and faculty leaders to explore how human-centered leadership can support their teaching in the middle of rapid technological change.

Grounded in a six-pillar leadership model that encompasses conscious self-awareness, relational intelligence, ethical influence, adaptive growth, transparent communication, and empowered action, this session …

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Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan Jun 2026

Learning In Infants Using Intrinsically Motivated Goal Conditioned Reinforcement Learning, T I Darsan

Master’s Dissertations

Traditional artificial intelligence models learn by passively digesting large datasets. In contrast, human infants discover skills by actively interacting with their bodies and environments without explicit external rewards. This thesis introduces the Composer Architecture, a machine learning framework designed to mimic this autonomous, open-ended development. The Composer architecture operates in a multi-stage loop, the latent model using Contrastive Learning Through Time (CLTT) to compress high-dimensional raw data from visual, proprioceptive, and touch sensors into a low-dimensional space. To preserve data relationships and prevent topological collapse, a Softmax activation forces these latent representations to lie smoothly on a probability simplex. A …

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An Efficient Hierarchical Deployment Of Sensors For K-Coverage In Planner Wireless Sensor Network, Abhay Raj Singh Jun 2026

An Efficient Hierarchical Deployment Of Sensors For K-Coverage In Planner Wireless Sensor Network, Abhay Raj Singh

Master’s Dissertations

Ensuring reliable sensing coverage is a fundamental challenge in wireless sensor networks (WSNs), particularly when multiple sensors are monitoring each location to provide robustness against node failures. In this work, we address the problem of deterministic k-coverage in planar WSN by proposing a hierarchical triangular lattice-based deployment strategy that organizes sensor locations across di↵erent refinement levels and guarantees coverage of every point in the sensing domain by at least k sensors. Each lattice is three-colorable, and selective activation of color classes ensures adjustable coverage guarantees. We prove that activating a single color class at refinement level t guarantees at least …

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State Government, The Forgotten Cyber Actor, Joshua D. Strubel Jun 2026

State Government, The Forgotten Cyber Actor, Joshua D. Strubel

Doctoral Dissertations and Projects

Cyber incidents are among the most pervasive threats facing the United States, with the FBI recording over 859,000 reported attacks and an estimated $16.6 billion in losses in 2024 alone. Despite widespread recognition that effective cyber defense requires a whole-nation approach, the existing research literature overwhelmingly focuses on federal policy, leaving state governments as largely overlooked actors. This study addresses that gap by examining the research question: How does state cybersecurity policy affect malicious cyber actors' frequency of operations? Drawing on multilinear regression analysis augmented by Random Forest machine learning models, this study evaluates the relationship between state-level cyber deterrence …

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Adaptive Intervention Strategies In Co-Evolving Multiplex Networks: A Reinforcement Learning Approach To Real-Time Misinformation Containment, Anjali Ashokrao Bhadre Dr., Harshvardhan Prabhakar Ghongade Dr. Jun 2026

Adaptive Intervention Strategies In Co-Evolving Multiplex Networks: A Reinforcement Learning Approach To Real-Time Misinformation Containment, Anjali Ashokrao Bhadre Dr., Harshvardhan Prabhakar Ghongade Dr.

Northeast Journal of Complex Systems (NEJCS)

The growing transmission of misinformation via social media creates serious challenges to public health, democracy and social cohesion. To date, methods used to contain misinformation rely upon static representations of networks and set rules for interventions. In contrast, this study presents the first Multiplex Adaptive Reinforcement Intervention Network (MARIN), a framework for real-time adaptive intervention in the context of dynamic misinformation transmission using co-evolving multiplex networks and deep reinforcement learning. Unlike past studies that have assumed static network structures, MARIN has the ability to allow for dynamic changes in network topology as a result of both misinformation transmission and intervention …

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Tinyvgg-Based Real-Time Degradation Classification For Adverse Driving Scenes Using A Newly Collected Iraqi Driving Dataset, Yousif N. Abbas, Matheel E. Abdulmunim, Nada H. Ali, Ismail A. Mageed Jun 2026

Tinyvgg-Based Real-Time Degradation Classification For Adverse Driving Scenes Using A Newly Collected Iraqi Driving Dataset, Yousif N. Abbas, Matheel E. Abdulmunim, Nada H. Ali, Ismail A. Mageed

Journal of Soft Computing and Computer Applications

Environmental conditions such as low-light at night, fog scattering, glare artifacts, rain streaks, and rain smear distortions are significant issues of camera-based perception in Autonomous Vehicles (AVs). These degradations alter the statistics of the scene, mask structure, introduce non-uniform noise, and adversely affect downstream vision processes, including detection and tracking. To overcome this shortcoming, this paper presents a lightweight TinyVGG-based degradation classification system that runs in real time. The network extracts discriminative spatial features with hierarchical convolutional encoding and projects them to a lower-dimensional semantic representation with fully connected layers and a multi-class predictor based on SoftMax. In addition, a …

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Improving Approach Of Evolutionary Strategies For Clustering Technique Enhancement, Duaa Mahde Saleh, Hasanen S. Abdullah, Ahmad Zamsuri Jun 2026

Improving Approach Of Evolutionary Strategies For Clustering Technique Enhancement, Duaa Mahde Saleh, Hasanen S. Abdullah, Ahmad Zamsuri

Journal of Soft Computing and Computer Applications

The existence of the information has been the essential aspect of the whole society. Information is concentrated in all forms to be effectively utilized. Clustering — an unsupervised learning technique. It is based on data similarity that gives rise to issues in collection, challenges and instability in data structure. It proposes an advanced evolutionary method by combining two approaches. Firstly, it adopts the evolutionary approach and integrates the advantages between two methods to design one. Among them are Differential Evolution (DE) and Genetic Algorithm (GA), Evolutionary Strategy (ES) and Genetic Programming (GP), and Evolutionary Programming (EP) and Particle Swarm Optimization …

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