Artificial Intelligence and Robotics Commons^™

Gambaran Generasi Z Yang Kesepian Dalam Penggunaan Chat Ai Sebagai Pemenuhan Kebutuhan “Someone To Talk”, Ikhwanul Ihsan Armalid, Febty Zahra Arsiwi, Qisthi Fathiyyah, Ratri Mayzakky Afra Syahida

Jurnal Psikologi Sosial

This study aims to understand the experiences of Generation Z individuals who experience loneliness in utilizing Chat AI to fulfill their need for someone to talk to within a socio-emotional context. The study employed a qualitative approach using a phenomenological method involving six Generation Z participants aged 18 to 25 who had used Chat AI for emotional sharing or venting. Data were collected through semi-structured interviews and analyzed using thematic analysis. The thematic analysis yielded six main themes: the dynamics of Generation Z social interactions, experiences of loneliness in social life, patterns of Chat AI usage, Chat AI as a …

Closing The Interpretability Gap: Explainable Ml-Based Malware Detection For Defensive Cyberspace Operations, Tashi Stirewalt, Sean Hodgson, Puumaaya Tahiru, Assefaw Gebremedhin

Military Cyber Affairs

This paper presents an end-to-end, explainable malware triage pipeline designed for defense-oriented cyber operations. It combines high-performance static detection methods with analyst-centered interpretability. Utilizing the EMBER 2024 Windows PE subset, we train and evaluate four classifiers and select LightGBM as the production model based on its predictive performance, inference efficiency, and compatibility with exact tree-based attribution. The deployed system consists of four sequential components: PE feature extraction, malware probability scoring, dual explainability (using SHAP and LIME), and large language model (LLM) report generation, all integrated within a Flask web interface. On a temporal test set of 1,080,000 samples, LightGBM achieves …

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 …

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 …

When Does Global Search Pay For Itself? A Measured Exploration Cost And Energy Break-Even Analysis Of A Metaheuristic Search Controller In Solar Energy Systems, Mohamed Ali Muammar Ezgour

Communications of the IIMA

Autonomous energy systems increasingly delegate the choice of operating point to embedded search algorithms, trading a fast local optimizer that can settle on a wrong point against a slower global search that guarantees the right one at a measurable cost. This paper reframes maximum power point tracking under partial shading as that decision and measures its economics on a fixed photovoltaic plant in MATLAB/Simulink. A Hippopotamus Optimization global search handed over to incremental conductance is compared with incremental conductance alone across seventeen initial duty cycles and thirty random seeds. The hybrid reached the global peak in all thirty seeds, whereas …

From Data To Victory: The Race For Analytic Superiority In Warfare, Robert Grossman, Emily Goldman

Joint Force Quarterly

Artificial intelligence technologies have reached a tipping point after decades of development. They are diffusing widely across defense and national security applications. Twenty-first century warfighters rely on analytic models in all systems, at all echelons, and in all domains. As more powerful models built on ever larger data sets become ubiquitous, militaries are in a new competition to deploy artificial intelligence. Operational art must embrace “analytic superiority.” This is the operational advantage from collecting and ingesting data, building robust models and computing infrastructure, deploying the models into operational systems, and denying adversaries' ability to do the same

This article explains …

From Data To Decision-Making: The Role Of Local Digital Twins In Cross-Domain Management Within Municipalities – A Research-In-Progress Study In Veenendaal, Diana M.E. Boekman, Koen Smit, Guido Ongena, Rob Peters

Communications of the IIMA

Municipalities are facing increasingly complex, interconnected challenges in areas like housing, climate adaptation, mobility, and social policy. Local Digital Twins (LDTs) are seen as a promising tool to make this complexity more understandable and support decision-making. At the same time, both literature and practice show that few initiatives get past the pilot phase, even though getting through that phase is essential for successful long-term adoption.

This paper presents a research-in-progress study on the development and application of an implementation method for LDT technology within the municipality of Veenendaal, based on human values rather than driven by technological possibilities. Based on …

From Dissertation To Deployment: A Unified Software Platform Operationalizing Clinical-Prediction And Sequential-Security Ai For Healthcare, Olsi Shehu, Damiana Teliti, Jasmin Kevrić, Bekir Karlik

Communications of the IIMA

Advances in machine learning for healthcare are abundant, yet most validated models remain confined to research notebooks and never reach secure, usable clinical software. This paper addresses that deployment gap by presenting a unified, security-hardened software platform that operationalizes two complementary streams of doctoral research inside a single, role-based hospital information system. The first stream contributes a clinical-prediction capability: an ultra-hybrid ensemble that couples a quantum-inspired feature transformation, particle-swarm feature selection, and calibrated soft voting for cancer-outcome prediction (96.41% accuracy, AUC-ROC 0.983 on TCGA-BRCA), survival stratification, multi-cancer generalization, and pharmacogenomic drug-response classification (89.31% mean accuracy across 25 compounds). The second …

Analysis Of The Throttle Settings Under Uncertain Information, Latafat Gardashova, Nihad Afandi

Chemical Technology, Control and Management

Although classical fuzzy logic controllers are capable of modelling non-linear control systems, they fail to consider the reliability of linguistic information, sensor measurements, and expert knowledge. In this paper, an intelligent controller based on the use of Z-numbers is developed for steam-turbine throttle control. Linguistic information and its confidence degree are considered simultaneously in such a controller. The temperature and pressure values are taken as input variables, while the throttle rotation is selected as the controller output variable. At first, the Z-number representation system is constructed to include the credibility of linguistic measurements and control rules. Then, a Mamdani Type-1 …

Nonlinear System Identification Based On Fuzzy Radial Basis Neural Network With Multi-Connected Weight Connections, Kabul Khudaybergenov

Chemical Technology, Control and Management

This paper builds on our earlier radial basis function network with multiple connections (RBFMC) by placing it within a fuzzy inference framework for nonlinear system identification. The idea is inspired by the diversity of neurotransmitters found in biological neurons: instead of a single hidden-to-output weight, RBFMC gives each hidden unit a multi-dimensional connection whose components act as independent filters. Once fuzzy logic is added, each hidden neuron becomes a fuzzy rule, and its antecedent is built from several Gaussian membership functions, one per connection. The resulting Fuzzy RBFMC produces an interpretable, multi-filter description of local regions of the input space …

Energy Security Strategy Empowered By Artificial Intelligence, Qiang Ji, Jiaofeng Pan, Yu Song

Bulletin of Chinese Academy of Sciences (Chinese Version)

Against the backdrop of unprecedented changes in a century, geopolitical restructuring has led to the fragmentation of energy game camps, climate change has impacted the resilience of energy infrastructure, and energy transformation has promoted the multidimensional and coordinated expansion of security connotations. Artificial intelligence, with its core advantages such as optimizing geopolitical risk prevention and control, enhancing infrastructure protection, improving energy system efficiency, and accelerating the integration of renewable energy, has promoted the shift of energy security strategy from experience driven to data-driven intelligence, achieving comprehensive risk identification, dynamic evaluation, collaborative response, and full chain monitoring, significantly improving the efficiency, …

Large Models Empowering Cybersecurity: Opportunities And Challenges, Zhuofeng He, Dongbin Hu, Yige Yuan

Bulletin of Chinese Academy of Sciences (Chinese Version)

Cybersecurity serves as a critical pillar for national security and social stability. Large models in cybersecurity are emerging as key enablers for the intelligent transformation of cyber offense and defense systems. As one of the most advanced core technologies in artificial intelligence, large models are introducing new research directions and application paradigms in the cybersecurity domain. This study systematically reviews the current landscape of cybersecurity-oriented large model applications and products, and explores their deployment scenarios in practice. It further analyzes the development trends in model capabilities, industry ecosystems, and trustworthiness, while identifying major practical challenges such as data privacy protection, …

Critical Core Technology Breakthroughs In Large-Scale Models: Industrialization Strategies And Policy Implications, Zhongqi Wu, Yinshan Liu, Tao Dai, Xiaolong Zheng

Bulletin of Chinese Academy of Sciences (Chinese Version)

As a pivotal direction for breakthroughs in key core technologies within the artificial intelligence domain, large-scale models hold strategic significance in securing national scientific and technological sovereignty. This study employs a multidimensional framework encompassing “technological breakthroughs, industrial transformation, and governance policies” to systematically investigate the developmental trajectories and industrialization bottlenecks of large-scale models. At the technological level, while large-scale models exhibit exponential growth in parameter scale and computing power demands, they face critical challenges including the scarcity of high-quality data, insufficient transfer learning capabilities, and reliability-explainability trade-offs. Industrially, these models are reshaping the global industrial chain landscape through a dual-track …

Evolutionary Trajectory Of Ai And Robotics Integration, Jiannan Zhu, Jianfeng Guo, Siyao Liu, Qi Cao

Bulletin of Chinese Academy of Sciences (Chinese Version)

The convergence of artificial intelligence (AI) and robotics is a cornerstone for the intelligent transformation of the physical world. This study conducts a systematic analysis of over 230,000 publications from the Web of Science and WIPO databases between 1982 and 2025 to dissect the evolutionary trajectory of AI and robotics integration since the 20th century. The findings identify four distinct developmental stages—independent exploration, functional coupling, primary intelligence, and intelligent symbiosis—while delineating the key technological breakthroughs and paradigm characteristics of each phase. Furthermore, seven core research thrusts are distilled, including motion planning and autonomous decision-making and perception & environmental understanding. An …

The Honored Children Of Adam: A Muslim Reading Of Magnifica Humanitas In The Age Of Artificial Intelligence, Iqbal Akhtar

The Journal of Social Encounters

No abstract provided.

Partial Coalitions And Peacemaking As Metaphor, Julie Hawke

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas, The ‘Universal Destination Of Goods,’ And Social Movements, John Sniegocki

The Journal of Social Encounters

No abstract provided.

Leo’S Choices, Katherine G. Schmidt

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas And The Obsolescence Of Just War, Noreen Herzfeld

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas For The Marginalized, Nabila Feroz Bhatti

The Journal of Social Encounters

No abstract provided.

Humanity’S Grandeur In The Balance: Theological Reflections On Magnifica Humanitas, William L. Portier

The Journal of Social Encounters

No abstract provided.

Magnifica Humanitas: Not Just About Artificial Intelligence, John Ashworth

The Journal of Social Encounters

No abstract provided.

The Fridge And The Drone: A Reflection From The Perspective Of Palestinian Liberation Theology On Magnifica Humanitas, Omar Haramy

The Journal of Social Encounters

No abstract provided.

Artificial Intelligence And The Rediscovery Of The Human: An Islamic Reflection On Magnifica Humanitas, Mazhar Ali Bari, Biliana Popova

The Journal of Social Encounters

No abstract provided.

Riyadh Charter On Artificial Intelligence For The Islamic World, - Islamic World Educational, Scientific And Cultural Organization (Icesco), - Saudi Data And Artificial Intelligence Authority (Sdaia)

The Journal of Social Encounters

The Riyadh Charter on Artificial Intelligence for the Islamic World was launched by the Islamic World Educational, Scientific and Cultural Organization (ICESCO) and the Saudi Data and Artificial Intelligence Authority (SDAIA) in September 2024, in collaboration with the Saudi National Commission for Education, Culture, and Science, during the third Global AI Summit (GAIN Summit) in Riyadh.

The Charter has been widely recognized and endorsed by Islamic scholars and policymakers. During the 26th Session of the Council of the International Islamic Fiqh Academy, it was highlighted as a moral and strategic compass for AI technologies, addressing the limitations of existing international …

Preliminary Report - Evidence-Based Assessment Of Opportunities, Risks And Impacts Of Artificial Intelligence, - United Nations Independent International Scientific Panel On Ai

The Journal of Social Encounters

No abstract provided.

Encyclical Letter "Magnifica Humanitas", - Pope Leo Xiv

The Journal of Social Encounters

No abstract provided.

Introduction: Essays On Artificial Intelligence And Magnifica Humanitas, Ron Pagnucco

The Journal of Social Encounters

No abstract provided.

Emergency Risk Dispatch For Integrated Electricity-Heat Systems Under Typhoon Disasters, Tongchui Liu, Lian Tan, Dongxuan Bao, Lanting Zeng, Pengfei Hou, Ronghua Ling

Journal of System Simulation

Abstract: The spatiotemporal randomness of typhoon movement paths leads to uncertain operational risks for integrated electricity-heat systems (IEHS), making it difficult to balance system risk controllability and dispatch economy. To tackle this problem, an emergency risk dispatch (ERD) method for IEHS under typhoon disasters is proposed. An ERD model for IEHS under typhoon disasters is established within the model predictive control framework. Based on the uncertainty of typhoon wind speed prediction, a moment-based ambiguity set for uncertain equipment component failures is constructed, and a distributionally robust chance-constrained ERD model is formulated. An approximation method based on worst-case conditional value-at-risk (WC-CVaR) …

Bi-Level Coordinated Scheduling And Optimization Of Power Systems Based On Stackelberg-Gmo, Yuanxing Zhang, Jianfeng Li, Taoyong Li, Linjuan Zhang, Jincheng Liu, Bin Li

Journal of System Simulation

Abstract: , To balance the interests of the power grid and the demand side, and achieve coordinated improvements in system economic efficiency, environmental friendliness, and renewable energy accommodation capacity, this paper proposes a bi-level coordinated scheduling model based on the Stackelberg game and the GMO. A leader-follower game model incorporating carbon emission constraints and multi-scenario stochastic constraints for photovoltaic generation is constructed, with the grid operator as the leader and EVs/V2G and energy storage as the followers, resolving the core contradiction between global optimization and individual rationality. The spatio-temporal stochastic characteristics of EV travel, the cycle life of energy storage …