Robust Color Image Encryption Scheme Based on RSA via DCT by Using an Advanced Logic Design Approach by Khalid Kadhim Jabbar, Fahmi Ghozzi, Ahmed Fakhfakh

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The canyon of Haidamatskyi Iar in the village of Busha: Geotourism assessment by Yulian Braychevskyy, Volodymyr Korinnyi, Olga Kovtoniuk, Nataliia Pohorilchuk

“…For each algorithm, we presented results as a percentage of the maximum for easier comparison. …”
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Jet substructure probe on scalar leptoquark models via top polarization by Anupam Ghosh, Partha Konar, Tousik Samui, Ritesh K. Singh

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A learning trajectory for developing computational thinking in prospective mathematics teachers through Python programming in Google Colab by Edi Irawan, Moh. Khoridatul Huda, Ratni Purwasih

“…The results showed that HLT, designed in stages, improved the four main components of CT: decomposition, abstraction, pattern recognition, and algorithmic thinking. The students experienced improvements in breaking down problems, devising more efficient solutions, recognising patterns in code structures, and systematically designing algorithms. …”
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Development and Prospects of National Intelligent System for Testing General Language Competencies Deployed Through Neural Network Solutions by E. M. Bazanova, A. V. Gorizontova, N. N. Gribova, T. M. Chikake, A. V. Samosyuk

“…The process of ISTOK development implied, apart from writing test items, putting together databases of writing and speaking assignments marked by professional assessors and assessment criteria for productive skills, as well as algorithms to identify various types of mistakes with the help of artificial intelligence. …”
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A redundant weight removal method inspired by specific immunotherapy for boosting transfer learning security by Qing Huang, Hongli Deng, Junxiang Wang, Tao Yang, Bochuan Zheng

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ADF-SL: An Adaptive and Fair Scheme for Smart Learning Task Distribution by Ahmed A. Al-Saedi, Veselka Boeva

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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

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Pioneering CPMI framework for accurate state-of-health assessment in Lithium ion battery power management using FBG sensors by Taher M. Ghazal, Ali Q. Saeed, Mosleh M. Abualhaj, Taj-Aldeen Naser Abdali, Munir Ahmad

“…The proposed system employs a support vector-based classification algorithm that categorizes operational states based on FBG sensor data streams, identifying deviations from optimal temperature and voltage ranges. …”
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TRAINING SYSTEM OF FUTURE SPECIALISTS: QUALITY CONTROL by Vladimir A. Romanov, Valentina N. Kormakova, Elena N. Musaelian

“…The strategy of the development of the process of quality control training in educational professional organizations and a predictive model of the system of quality control training for future engineers and workers have been created on the analysis and synthesis of a quantitative specification of the quality, the obtained experience and success in control training of future specialists in educational professional organizations in recent economic and educational conditions.Scientific novelty. …”
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Use of artificial intelligence in the diagnosis, treatment and surveillance of patients with kidney cancer by E. Yu. Timofeeva, С. R. Azilgareeva, A. O. Morozov, M. S. Taratkin, D. V. Enikeev

“…AI finds its application in histopathological evaluation: the AI model reaches 100.0% sensitivity and 97.1% specificity in the differential diagnosis of normal tissue from RCC. AI model algorithms may be used to identify patients at high risk of relapse requiring long-term follow-up, as well as to develop individual treatment and follow-up strategies. …”
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A joint three-plane physics-constrained deep learning based polynomial fitting approach for MR electrical properties tomography by Kyu-Jin Jung, Thierry G. Meerbothe, Chuanjiang Cui, Mina Park, Cornelis A.T. van den Berg, Stefano Mandija, Dong-Hyun Kim

“…To estimate tissue electrical properties, various reconstruction algorithms have been proposed. However, physics-based reconstructions are prone to various artifacts such as noise amplification and boundary artifact. …”
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Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
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Energy-efficient strategy for data migration and merging in Storm by Yonglin PU, Jiong YU, Liang LU, Ziyang LI, Chen BIAN, Bin LIAO

“…Storm is suffering the problems of high energy consumption but low efficiency.Aiming at this problem,the resource constraint model,the optimal principle of data reorganization in executors and node voltage reduction principle were proposed based on the analysis of the architecture and topology of Storm,and further the energy-efficient strategy for data migration and merging was put forward in Storm(DMM-Storm),which was composed of resource constraint algorithm,data migration and merging algorithm as well as node voltage reduction algorithm.The resource constraint algorithm estimates whether work nodes are appropriate for data migration according to the resource constraint model.The data migration and merging algorithm designs an optimal method to migrate data according to the the optimal principle of data reorganization in executors.The node voltage reduction algorithm reduces voltage of work nodes according to node voltage reduction principle.The experimental results show that the DMM-Storm can reduce energy consumption efficiently without affecting the performance of cluster compared with the existing researches.…”
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Comparison of Probabilistic Chain Graphical Model-Based and Gaussian Process-Based Observation Selections for Wireless Sensor Scheduling by Qi Qi, Yi Shang

“…We compare their performances in terms of predictive accuracies for the unobserved time points based on their selections of observations. …”
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Enhancing Real-Time Emotion Recognition in Classroom Environments Using Convolutional Neural Networks: A Step Towards Optical Neural Networks for Advanced Data Processing by Nuphar Avital, Idan Egel, Ido Weinstock, Dror Malka

“…An experimental validation was conducted in a classroom with 45 students, demonstrating that the level of understanding in the class as predicted was 43–62.94%, and the proposed CNN algorithm (facial expressions detection) achieved an impressive 83% accuracy in understanding students’ emotional states. …”
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Modeling Topic-Specific Influential Users in QA Forums Using Association Rule Mining by Umar Ishfaq, Tassawar Ali, Ali Daud, Mohammed Alreshoodi, Azeem Irshad

“…This paper incorporates association rule mining (ARM) based algorithms, that are mostly used for market-basket analysis, for exploring the behavior of users and predict their participation in social interactions. …”
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Multi-Model Demand Forecasting in Water Distribution Network Districts by Enrico Creaco, Carlo Giudicianni, Manuel Herrera

“…The first two modelling elements working in parallel are a pattern-based algorithm and a Random Forest model. By varying the algorithm setting and predictors, 42 algorithms are constructed and calibrated using demand and weather data in the previous weeks to the generic <i>n</i>-th week, when the objective is the prediction of the hourly demand pattern in the <i>n</i> + 1-th week. …”
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Non-invasive ML methods for diagnosis of congenital heart disease associated with pulmonary arterial hypertension by Yuyang Gao, Pengyue Ma, Jiahua Pan, Hongbo Yang, Tao Guo, Weilian Wang

“…Pre-processing in both algorithms focuses on segmentation of heart sounds into discrete cardiac cycles. …”
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A multi-objective master–slave methodology for optimally integrating and operating photovoltaic generators in urban and rural electrical networks by Jhony Andrés Guzmán-Henao, Rubén Iván Bolaños, Brandon Cortés-Caicedo, Luis Fernando Grisales-Noreña, Oscar Danilo Montoya, Jesús C. Hernández

“…The results demonstrated the effectiveness of these algorithms. NSGA-II achieved the best performance, with reductions of 32.84% in energy losses and 42.41% in operating costs (with standard deviations of 0.21% and 0.39%, respectively) for the urban system; and reductions of 21.87% in energy losses and 43.36% in operating costs (with standard deviations of 0.07% and 0.24%, respectively) for the rural system. …”
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