Shelter Experiences of the Homeless People: “One Wants To Feel Cared For” by Cengizhan Aynacı, Yusuf Genç

“…The data obtained from these semi-structured interviews were analysed using descriptive and content analysis methods. …”
Get full text

Automated Wall Moisture Detection in Heritage Sites Based on Convolutional Neural Network (CNN) for Infrared Imagery by Yu-Chieh Chu, Ya-Yun Huang, Chen-Yu Ye, Shih-Lun Chen

“…However, its reliance on manual interpretation by experts makes the process both time-consuming and costly. …”
Get full text

Artificial intelligence and chordoma: A scoping review of the current landscape and future directions by Eddie Guo, Rafael D. Sanguinetti, Lyndon Boone, Jiawen Deng, Husain Shakil, Mehul Gupta

“…Future research should focus on collaborative efforts for larger, diverse datasets with external validation cohorts, interpretable multimodal models, and validation through prospective clinical trials.…”
Get full text

MDFT-GAN: A Multi-Domain Feature Transformer GAN for Bearing Fault Diagnosis Under Limited and Imbalanced Data Conditions by Chenxi Guo, Vyacheslav V. Potekhin, Peng Li, Elena A. Kovalchuk, Jing Lian

“…In industrial scenarios, bearing fault diagnosis often suffers from data scarcity and class imbalance, which significantly hinders the generalization performance of data-driven models. While generative adversarial networks (GANs) have shown promise in data augmentation, their efficacy deteriorates in the presence of multi-category and structurally complex fault distributions. …”
Get full text

Revolutionizing Sperm Analysis with AI: A Review of Computer-Aided Sperm Analysis Systems by Francisco J. Baldán, Diego García-Gil, Carlos Fernandez-Basso

“…By employing a spectrum of techniques, from classic machine learning (ML), often valued for its interpretability and efficiency with structured data, to deep learning (DL), which excels at extracting intricate features directly from image and video data, the field now achieves more accurate, automated, and high-throughput evaluations. …”
Get full text

Data-Efficient Sowing Position Estimation for Agricultural Robots Combining Image Analysis and Expert Knowledge by Shuntaro Aotake, Takuya Otani, Masatoshi Funabashi, Atsuo Takanishi

“…These findings highlight the potential of interpretable, low-data machine learning models for rapid adaptation to complex agroecological systems and demonstrate a practical approach to combining structured human expertise with sensor-based automation in biodiverse farming environments.…”
Get full text

Deep Residual Network With Integrated StarDist Nuclei Segmentation for Papillary Thyroid Cancer Identification: A Pathologist-Inspired Approach by Nabila Husna Shabrina, Dadang Gunawan, Mia Rizkinia, Agnes Stephanie Harahap, Mohammad Ikhsan, Rifai Chai, Maria Francisca Ham

“…This study proposes a deep residual network with integrated StarDist nuclei segmentation to enhance the model’s ability to focus on critical cellular structures when making predictions. …”
Get full text

Artificial neural network algorithm for time dependent radiative Casson fluid flow with couple stresses through a microchannel by Pradeep Kumar, Felicita Almeida, Qasem Al-Mdallal

“…It helps in analysing large datasets which might be difficult to accomplish by conventional models. They help in modelling and analysing complex fluid flow problems and when properly trained they help in predicting the flow structures. …”
Get full text

Predictive Framework for Sustainable Engineering through Machine Learning and Cross-Sector Collaboration by Choudhary Abhik, Adhikari Upasana, Roy Dipankar, Gupta Subir, Roy Priyanka, Bhaduri Aparna

“…An Extra Trees Classifier was trained to perform binary classification of project success deemed as primary indicators, evaluating performance through accuracy, precision, recall, F1 score, log loss, and MSE. The model achieved 96% accuracy and 0.733 F1 score. Feature importance analysis corroborated interpretability of model predictions. …”
Get full text

Verification of Opacity Under a <i>K</i>-Delay Orwellian Observation Mechanism by Jiahui Zhang, Kuize Zhang, Xiaoguang Han, Zhiwu Li

“…In this paper, instead of adopting a fully static observation model or a fully dynamic observation model, we use a novel Orwellian-type observation model to study the verification of the current-state opacity (CSO), where the observability of an unobservable event can be re-interpreted once certain/several specific conditions are met. …”
Get full text

Epistemological Transformation of ʿUrf in the DSN-MUI Fatwa on E-Commerce: A Maqāṣid al-Sharīʿah Based Analysis by Sanuri, Nafi' Mubarok, Suqiyah Musafa’ah, Yoga Irama

“…Employing a qualitative-normative approach, the research analyzes Fatwa No. 146/2021, issued by the National Sharia Council of the Indonesian Ulema Council (DSN-MUI), classical and contemporary fiqh sources, and emerging digital transaction models. It integrates concepts from uṣūl al-fiqh, maqāṣid al-sharī‘ah, and socio-philosophical reasoning to reconceptualize ʿurf as a dynamic category of legal interpretation. …”
Get full text

Enhanced Learning Behaviors and Ability Knowledge Tracing by Fanglan Ma, Changsheng Zhu, Peng Lei, Peiwen Yuan

“…The LBAKT model is structured into four layers: embedding, learning, forgetting, and predicting. …”
Get full text

Lithuania's Poles and Russians: two different perspectives by Virginijus Savukynas

“…Therefore, according to the author, the aim of the article is to show how and to what extent does the culture, which is understood as a constellation of symbolic structures and structures of meaning, determine the structures of social reality. …”
Get full text

Quo Vadis „Living Human Treasures”? by Nicolae Lupu, Mihail Ovidiu Tănase, Petronela Tudorache

“…Furthermore, it would avoid the exhausting movements of artisans at the various trade fairs, being preferable to receive the audience in their personal household tranquility. A series of semi structured personal interviews with some LHT confirm this hypothesis. …”
Get full text

Predicting Clay Swelling Pressure: A Comparative Analysis of Advanced Symbolic Regression Techniques by Esteban Díaz, Roberto Tomás

“…These methods provide interpretable results as equations, unlike standard machine learning models. …”
Get full text

Vertical Slowness-Constrained Joint Anisotropic Parameters and Event-Location Inversion for Downhole Microseismic Monitoring by Congcong Yuan, Jie Zhang

“…Ignoring anisotropy can result in significant distortions in microseismic event locations and their interpretation. Although methods exist to simultaneously invert anisotropic parameters and event locations using microseismic arrival times, the results heavily depend on accurate initial models and sufficient ray coverage due to strong trade-offs among multiple parameters. …”
Get full text

Scene Graph and Natural Language-Based Semantic Image Retrieval Using Vision Sensor Data by Jaehoon Kim, Byoung Chul Ko

“…This confirms that the model effectively retrieves semantically relevant images by structurally interpreting complex scenes.…”
Get full text

Linguistics Specificity of Universities Prospectuses: A Corpus-Based Genre Analysis by Aiman Qaiser, Syed Shujaat Ali, Naveed-Ur-Rehman Khattak

“…This study investigates the specific lexical choices found in university prospectuses while examining the linguistic structures that define their textual characteristics and determining the genre type by comparing it with similar text types to understand the unique language features of these documents. …”
Get full text

Cyber intrusion detection using ensemble of deep learning with prediction scoring based optimized feature sets for IOT networks by Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Vaishali H. Kamble

“…Additionally, to enhance interpretability and support decision-making, we incorporate the Exploit Prediction Scoring System (EPSS), which evaluates prediction scores and provides detailed insights, thereby improving overall model performance. …”
Get full text

Architectural Gaps in Generative AI: Quantifying Cognitive Risks for Safety Applications by He Wen, Pingfan Hu

“…<b>Background</b>: The rapid integration of generative AIs, such as ChatGPT, into industrial, process, and construction management introduces both operational advantages and emerging cognitive risks. While these models support task automation and safety analysis, their internal architecture differs fundamentally from human cognition, posing interpretability and trust challenges in high-risk contexts. …”
Get full text