THE USE OF REMOTE SENSING TECHNIQUES FOR MODELING AND ANALYSIS OF THE URBAN EXPANSION OF AIN SALAH CITY IN THE ALGERIAN SAHARA BETWEEN 2000- 2023 by Ali SAIDOU, Saida MEFTAH

“…The study's findings have implications for urban planning and management, highlighting the need for sustainable urban development strategies to address concerns about traffic congestion, waste management, and public health issues. The study's use of machine learning algorithms and high-resolution satellite imagery provides valuable insights into the dynamics of urbanization in arid environments and can inform future urban planning and sustainable development strategies in similar regions.…”
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Making sense of transformer success by Nicola Angius, Pietro Perconti, Alessio Plebe, Alessandro Acciai

“…In particular, available experimental studies turned to test the theory of mind, discourse entity tracking, and property induction in NLMs are examined under the light of the functional analysis in the philosophy of cognitive science; the so-called copying algorithm and the induction head phenomenon of a Transformer are shown to provide a mechanist explanation of in-context learning; finally, current pioneering attempts to use NLMs to predict brain activation patterns when processing language are here shown to involve what we call a co-simulation, in which a NLM and the brain are used to simulate and understand each other.…”
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GREEN ECONOMY AND HOLISTIC PLANNING BY ARTIFICIAL INTELLIGENCEAPPLICATION by STEVOVIC IVAN, HADROVIĆ SABAHUDIN, JOVANOVIC MIHAILO

“…On the one hand, IT such as machine learning, data analytics, and optimization algorithms offer immense potential to enhance resource efficiency, optimize energy systems, and facilitate sustainable decision-making processes. …”
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Review of Methods and Models for Forecasting Electricity Consumption by Kamil Misiurek, Tadeusz Olkuski, Janusz Zyśk

“…The authors conducted a comparative analysis of various models, such as autoregressive models, neural networks, fuzzy logic systems, hybrid models, and evolutionary algorithms. Particular attention was paid to the effectiveness of these methods in the context of variable input data, such as weather conditions, seasonal fluctuations, and changes in energy consumption patterns. …”
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On the effect of sampling frequency on the electricity theft detection performance by Fatemeh Soleimani Nasab, Foad Ghaderi

“…Abstract Electricity theft is a common problem in many countries and affects the revenue of the electricity industry significantly. Recently, machine and deep learning techniques are being used widely to detect thieves by analysing the consumption patterns. …”
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Innovative AI Solutions for Water-Efficient Smart Irrigation in Agriculture by Saha Laboni, Dubey Ahilya

“…The proposed AI solutions are integrated platform of machine learning algorithms and sensor data, predictive analytics for the purpose to generate a water efficient irrigation framework reacts dynamically to the crops' needs and environmental conditions. …”
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Interpretable Identification of Dynamic Adaptive Streaming over HTTP (DASH) Flows Based on Feature Engineering by Arkadiusz Biernacki

“…The clustering used the most significant features to group similar traffic patterns. We employed the following three algorithms that represent different clustering methodologies: partition-based, density-based, and probabilistic approaches. …”
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Load Balancing and Server Consolidation in Cloud Computing Environments: A Meta-Study by Mohammed Ala'anzy, Mohamed Othman

“…Just considering energy-efficiency (that can be attained efficiently by consolidate the servers) may not be enough for real applications because it may cause problems such as unbalanced load for each Physical Machine (PM). Therefore, this paper surveys published load balancing algorithms that achieved by server consolidation via a meta-analysis. …”
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Review of Modern Forest Fire Detection Techniques: Innovations in Image Processing and Deep Learning by Berk Özel, Muhammad Shahab Alam, Muhammad Umer Khan

“…Furthermore, we explore the utilization of deep learning and machine learning in training intelligent algorithms to recognize fire patterns and features. …”
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Smart diabetes management: remote monitoring and predictive health insights by K.S. Smelyakov, I.A. Lurin, K.V. Misiura, A.S. Chupryna, T.V. Tyzhnenko, O.D. Dolhanenko, V.M. Repikhov

“…The use of deep learning and neural network algorithms enhances the accuracy of these predictions by capturing complex data trends over time. …”
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Drunk Driver Detection Using Thermal Facial Images by Chin-Heng Chai, Siti Fatimah Abdul Razak, Sumendra Yogarayan, Ramesh Shanmugam

“…This study aims to investigate and propose a machine learning approach that can accurately detect alcohol consumption by analyzing the thermal patterns of facial features. …”
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Comparison of Random Forest, XGBoost, and LightGBM Methods for the Human Development Index Classification by Yunna Mentari Indah, Rafika Aristawidya, Anwar Fitrianto, Erfiani Erfiani, L.M. Risman Dwi Jumansyah

“…Machine learning classification is an effective tool for categorizing data based on patterns, which is particularly useful in analyzing the Human Development Index (HDI) in Indonesia. …”
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Virtual Nurse for Detecting Suicide Risk Behaviors in Adolescents by Yohanes Tarigan

“…The Virtual Nurse uses machine learning algorithms to analyze user behavior, speech patterns, and interactions to identify signs of suicide risk. …”
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Discriminative graph regularized representation learning for recognition. by Jinshan Qi, Rui Xu

“…Feature extraction has been extensively studied in the machine learning field as it plays a critical role in the success of various practical applications. …”
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The calcitron: A simple neuron model that implements many learning rules via the calcium control hypothesis. by Toviah Moldwin, Li Shay Azran, Idan Segev

“…Theoretical neuroscientists and machine learning researchers have proposed a variety of learning rules to enable artificial neural networks to effectively perform both supervised and unsupervised learning tasks. …”
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Ai And Creative Research In Algerian Universities: Faculty Perspectives On Integration by Meryem Kehal

“…Notably, machine learning algorithms and natural language processing were identified as particularly beneficial. …”
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Design of intelligent English translation teaching system combined with bidirectional encoder representation by Shanshan Xu

“…In addition, the system integrates machine learning algorithms that analyze students' learning habits and error patterns to provide customized exercises and tutoring. …”
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Oligogenic analysis across broad phenotypes of 46,XY differences in sex development associated with NR5A1/SF-1 variants: findings from the international SF1next studyResearch in co... by Chrysanthi Kouri, Idoia Martinez de Lapiscina, Rawda Naamneh-Elzenaty, Grit Sommer, Kay-Sara Sauter, Christa E. Flück, Saygin Abali, Zehra Yavas Abali, S. Faisal Ahmed, Leyla Akin, Maricruz Almaraz, Laura Audí, Murat Aydin, Antonio Balsamo, Federico Baronio, Jillian Bryce, Kanetee Busiah, Maria Caimari, Núria Camats-Tarruella, Ariadna Campos-Martorell, Luis Castaño, Anna Casteràs, Semra Çetinkaya, Hedi L. Claahsen - van der Grinten, Martine Cools, Ines Costa, Fatma Feyza Darendeliler, Justin H. Davies, Isabel Esteva, Helena Fabbri-Scallet, Courtney A. Finlayson, Emilio Garcia, Beatriz Garcia- Cuartero, Alina German, Evgenia Globa, Gil Guerra-Junior, Julio Guerrero, Tulay Guran, Sabine E. Hannema, Olaf Hiort, Josephine Hirsch, Ieuan Hughes, Marco Janner, Uchenna Kennedy, Zofia Kolesinska, Katherine Lachlan, Anna Lauber-Biason, Jana Krenek Malikova, Dagmar L’Allemand, Nina Lenhnerr-Taube, Angela Lucas-Herald, Jamala Mammadova, Veronica Mericq, Isabel Mönig, Francisca Moreno, Julia Mührer, Marek Niedziela, Anna Nordenstrom, Burçe Orman, Sukran Poyrazoglu, Jose M. Rial, Meilan M. Rutter, Amaia Rodríguez, Tara Schafer-Kalkhoff, Sumudu Nimali Seneviratne, Maria Sredkova-Ruskova, LIoyd J.W. Tack, Rieko Tadokoro-Cuccaro, Ajay Thankamony, Mónica Tomé, Amaia Vela, Malgorzata Wasniewska, David Zangen, Nataliya Zelinska

“…Interpretation: These findings highlight the complex genetic landscape of DSD associated with NR5A1/SF-1, where in several cases, the use of advanced genetic testing and filtering with specific algorithms and machine learning tools revealed additional genetic hits that may contribute to the phenotype. …”
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Integration of Bulk and Single-Cell Transcriptomics Reveals BCL2L14 as a Novel IGKC+ T Cell-Associated Therapeutic Target in Breast Cancer by He J, Akhtar A, Li J, Wei Q, Yuan Y, Ran J, Ma Y, Chen D

“…To pinpoint key regulatory genes, we applied machine learning algorithms. Based on the hub genes identified, we constructed a prognostic risk model and developed a nomogram to aid clinical decision-making. …”
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Opportunities and Challenges of Brain-on-a-Chip Interfaces by Wenwei Shao, Weiwei Meng, Jiachen Zuo, Xiaohong Li, Dong Ming

“…Furthermore, the evolution of BoCI systems depends on a range of stimulation strategies and novel decoding algorithms, including artificial-intelligence-driven methods, which has expanded BoCI applications to pattern recognition and robotic control. …”
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