Explainable Recommender Systems Through Reinforcement Learning and Knowledge Distillation on Knowledge Graphs by Alexandra Vultureanu-Albişi, Ionuţ Murareţu, Costin Bădică

“…This study presents a novel framework, <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>X</mi><msup><mi>R</mi><mn>2</mn></msup><msup><mi>K</mi><mn>2</mn></msup><mi>G</mi></mrow></semantics></math></inline-formula> (X for explainability, first R for recommender systems, the second R for reinforcement learning, first K for knowledge graph, the second K stands for knowledge distillation, and G for graph-based techniques), with the goal of developing a next-generation recommender system with a focus on careers empowerment. To optimize recommendations while ensuring sustainability and transparency, the proposed method integrates reinforcement learning with graph-based representations of career trajectories. …”
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Dual-Ascent-Inspired Transformer for Compressed Sensing by Rui Lin, Yue Shen, Yu Chen

“…Notably, DAT achieves comparable PSNR to the ISTA-Net+ baseline within just one epoch, while competing methods require significantly more training time. …”
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Benefits and Challenges of AI-Based Digital Twin Integration in the Saudi Arabian Construction Industry: A Correspondence Analysis (CA) Approach by Aljawharah A. Alnaser, Haytham Elmousalami

“…However, several challenges hinder the realization of these benefits, including a lack of standardization of integrated DT and AI in construction projects, a lack of understanding of AI’s capabilities, a lack of logistics and the limited availability of IT infrastructure, and the complexity of AI algorithms. These findings underscore the transformative potential of integrating AI-driven DTs to optimize construction performance, improve decision-making, and address real-world complexities. …”
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Employing Streaming Machine Learning for Modeling Workload Patterns in Multi-Tiered Data Storage Systems by Edson Ramiro Lucas Filho, George Savva, Lun Yang, Kebo Fu, Jianqiang Shen, Herodotos Herodotou

“…Modern multi-tiered data storage systems optimize file access by managing data across a hybrid composition of caches and storage tiers while using policies whose decisions can severely impact the storage system’s performance. …”
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Harnessing AI and Quantum Computing for Revolutionizing Drug Discovery and Approval Processes: Case Example for Collagen Toxicity by David Melvin Braga, Bharat Rawal

“…By generating computational data, predicting the efficacy of pharmaceuticals, and assessing their safety, AI and quantum computing can accelerate and optimize the process of identifying potential drug candidates. …”
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Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS by Kaiyue Xia MM, Shupeng Chen MD, Yingjian Zeng MD, Nana Tang MD, Meiling Zhang MD

“…Introduction Drug-induced myelosuppression (DIM) is a serious side effect of several medications, particularly chemotherapy, immunosuppressants, and targeted therapies, which can lead to infections, anemia, and bleeding. While these drugs are effective, their adverse effects can disrupt treatment plans and reduce quality of life. …”
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Intelligent gear decision method for vehicle automatic transmission system based on data mining by Yong Wang, Jianfeng Zeng, Pengfei Du, Huachao Xu

“…Subsequently, dynamic programming algorithms are employed to optimize intelligent gear decisions. …”
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Beamforming Design for Dual-functional Radar-communication Systems with Holographic Metasurface Antennas by Guangyi CHEN, Ruoyu ZHANG, Hong REN, Yue MA, Chen MIAO, Wen WU

“…To tackle this nonconvex optimization challenge, we propose an alternating optimization algorithm based on fractional programming. …”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…This study aimed to optimize the performance of a novel electrotactile BCI by employing advanced feature extraction and machine learning techniques on sERP signals for the classification of users’ selective tactile attention. …”
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The effect of implementing parenteral nutrition guideline on growth and clinical outcomes in preterm infants: a comparative study by Majid Mahallei, Lida Gorbani, Mohammad Bagher Hoseini, Elnaz Shaseb, Bahareh Mehramuz, Khatereh Rezazadeh

“…The PRE group received individualized PN formulations based on clinician discretion, while the POST group received PN guided by a newly introduced, stepwise algorithmic protocol aiming to optimize early protein and energy intake. …”
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Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand by Wanjing Ma, Lei Wang, Lin Li

“…The solution algorithm employed the min–max robust optimization to tackle the uncertainty and the Pareto optimum to decide the solution under dual objectives. …”
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Does the COVID-19 pandemic affect the asset allocation performance? Evidence from a composite asset selection approach by Jung-Bin Su

“…For instance, the optimal portfolios are the Chinese yuan-Ethereum and Bitcoin-Ethereum for the pre-COVID-19 period, but the WTI-Ethereum for the COVID-19 period. …”
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Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department by Ning Dai, Lunjun Li, Kaixin Xu, Zhehao Lu, Xudong Hu, Yanhong Yuan

“…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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Application research of 3D virtual interactive technology in interactive teaching of arts and crafts by Mingqi Yao

“…For this reason, the research proposes an image denoising model based on convolutional neural network and wavelet transform, which adopts residual neural network structure and batch normalization algorithm, aiming at gradient explosion and gradient disappearance that may be caused by convolutional neural network, And the problem of low training efficiency has been optimized. …”
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An Inter-Regional Lateral Transshipment Model to Massive Relief Supplies with Deprivation Costs by Shuanglin Li, Na Zhang, Jin Qin

“…Specifically, JADE is employed in the first stage to allocate the volume of massive relief supplies, aiming to minimize deprivation costs, while IALNS optimizes intermodal routing in the second stage to minimize the weighted sum of transportation time and cost. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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External archive guided radial-grid multi objective differential evolution by Vikas Palakonda, Samira Ghorbanpour, Jae-Mo Kang, Heechul Jung

“…Abstract Differential evolution (DE) is a robust evolutionary algorithm for solving single-objective and multi-objective optimization problems (MOPs). …”
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A Deep Reinforcement Learning-Based Cooperative Guidance Strategy Under Uncontrollable Velocity Conditions by Hao Cui, Ke Zhang, Minghu Tan, Jingyu Wang

“…This method employs the multi-agent proximal policy optimization (MAPPO) algorithm to construct a continuous action space framework for intelligent cooperative guidance. …”
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Meta-learning assisted robust control of universal quantum gates with uncertainties by Shihui Zhang, Zibo Miao, Yu Pan, Sibo Tao, Yu Chen

“…The inner reinforcement learning network focuses on decision making for specific optimization problems, while the outer meta-learning network adapts to varying environments and provides feedback to the inner network. …”
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A fuzzy irregular cellular automata-based method for the vertex colouring problem by Mostafa Kashani, Saeid Gorgin, Seyed Vahab Shojaedini

“…The results suggest that the proposed method is able to achieve better results in terms of the minimum number of required colours and the execution time of the algorithm, compared to other peer algorithms.…”
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