A review of state-of-the-art resolution improvement techniques in SPECT imaging by Zhibiao Cheng, Ping Chen, Jianhua Yan

“…It delves into advancements in detector design and modifications, projection sampling techniques, traditional reconstruction algorithm development and optimization, and the emerging role of deep learning. …”
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Methodological approaches to prevention of radiation-induced skin reactions in neutron-photon therapy for malignant neoplasms by E. L. Choynzonov, V. A. Lisin, О. V. Gribova, V. V. Velikaya, Zh. А. Startseva

“…We used the dependence of the relative biological effectiveness (RBE) of neutrons on the dose and time-dose-fractionation model (tdF). the interaction of neutrons with various types of tissues was analyzed, and the algorithm for summing neutron and photon doses in neutronphoton therapy was developed.Results. …”
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Insurance claims estimation and fraud detection with optimized deep learning techniques by P. Anand Kumar, S. Sountharrajan

“…With accurate estimation of insurance claims, insurers can have good risk perceptions and disburse compensation within proper time, while fraud prevention helps deter massive monetary loss from fraudulent activities. …”
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<italic>DynaTrack</italic>: Low-Power Channel-Aware Dynamic Smartphone Tracking Using UWB DL-TDOA by Junyoung Choi, Sagnik Bhattacharya, Joohyun Lee

“…Based on the conducted experiments, we show that DynaTrack achieves 41% higher accuracy in NLOS conditions while having 46% lower power consumption in LOS conditions compared to existing methods from prior research.…”
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An Explainable CatBoost Model for Crater Classification Based on Digital Elevation Model by Minghao Zhu, Jialong Lai, Xiaoping Zhang, Yi Xu, Weidong He

“…In this study, we propose a machine-learning-based approach using the CatBoost algorithm to classify craters based on variables extracted from Digital Elevation Model (DEM) data. …”
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Replacing non-biomedical concepts improves embedding of biomedical concepts. by Enock Niyonkuru, Mauricio Soto Gomez, Elena Casarighi, Stephan Antogiovanni, Hannah Blau, Justin T Reese, Giorgio Valentini, Peter N Robinson

“…Embeddings were generated using the Word2Vec algorithm applied to a corpus of 10 million PubMed abstracts. …”
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A Distributed Magnetic Sensor Network: Vehicle Trajectory Tracking Based on Cellular Automaton by Xinpeng Yao, Yanli Sun, Mengfei Liu, Hua Wang, Zijian Wang, Wei Quan, Wen Rong

“…To address these challenges, this paper proposes a novel method that integrates a distributed wireless magnetic sensor network with a temporal-spatial correlation algorithm to associate vehicle signals from multiple sensors. …”
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FungID: Innovative Fungi Identification Method with Chromogenic Profiling of Colony Color Patterns by John Pouris, Konstantinos Konstantinidis, Ioanna Pyrri, Effie G. Papageorgiou, Chrysa Voyiatzaki

“…Our research underscores the promising role of deep learning algorithms in enhancing the understanding of the taxonomy and ecological functions of fungi that can be grown in pure cultures, while also emphasizing the importance of carefully assessing the scope and limitations of these methods.…”
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Research on Heating Load Prediction Model based on the Influence of Multiple Meteorological Elements using Deep Learning by Rui MIAO, Mingcai LI, Meiling SUN, Di PAN, Xifan ZHANG

“…Accurate heating load forecasting is crucial for enhancing the efficiency of district heating systems and improving indoor comfort in buildings.This study takes Tianjin， a major city in northern China， as a case study.Based on hourly heating load and meteorological data from the heating season in 2021 -2022， the impacts of comprehensive meteorological factors， such as temperature， wind speed， relative humidity， and solar radiation， on heating load is analyzed.An efficient short-term heating load prediction model is constructed using the Nonlinear Autoregressive with Exogenous Inputs （NARX） neural network algorithm.The results show that the hourly heating load that displays significant diurnal and monthly variations， has a notably negative correlation with temperature， weakly negative correlation with solar radiation， while the relationships with humidity and wind speed vary depending on the season.Compared to the prediction model considering only temperature， the model incorporating temperature， wind speed， relative humidity， and solar radiation together has better prediction performance， reducing the relative error by approximately 1.4%.By comparing the forecast results with the LSTM neural network prediction model， the NARX model significantly enhances prediction accuracy with decreasing the relative error by about 3.6%.…”
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Optional and mandatory assignment strategies for dynamic vehicle routing with time windows by Mustafa Demirbilek

“…Results show that MPA outperforms under tighter time windows and high-demand settings, while MPM demonstrates robust performance across broader conditions. …”
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Low-Light Image Enhancement Using CycleGAN-Based Near-Infrared Image Generation and Fusion by Min-Han Lee, Young-Ho Go, Seung-Hwan Lee, Sung-Hak Lee

“…Experimental results demonstrate that the proposed method outperforms conventional algorithms, delivering superior quality and detail retention. …”
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Organic Agriculture Comprehension of Soil Agriculture Farmers in Amasya Province of Turkey by Mehmet Aksoy, Başaran Karademir, İbrahim Hakkı Kadirhanoğulları

“…According to the survey data, while the farmers reported that they received the information about Organic Agriculture from TV-radio and the internet to a large extent (58.5%), a very small percentage (11%) stated that they received training. …”
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Day-Ahead Scheduling of IES Containing Solar Thermal Power Generation Based on CNN-MI-BILSTM Considering Source-Load Uncertainty by Kun Ding, Yalu Sun, Boyang Chen, Jing Chen, Lixia Sun, Yingjun Wu, Yusheng Xia

“…The validity of the proposed model is verified by algorithm prediction simulation and day-ahead scheduling experiments under different configurations.…”
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Renal failure in patients with hematological malignancies (literature review) by E. G. Gromova

“…Antitumor therapy in presence of renal failure is limited, and in some cases impossible, while the renal function recovery is associated with an increase in survival.Organ damage in oncohematological patients can be a manifestation of paraneoplastic syndromes. …”
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An energy-based numerical continuation approach for quasi-static mechanical manipulation by Lin Yang, Huu-Thiet Nguyen, Chen Lv, Domenico Campolo, Franco Cardin

“…Traditional motion planning techniques, while having shown their success in collision-free scenarios, may not handle manipulation tasks effectively because they typically avoid contact. …”
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Memory consolidation from a reinforcement learning perspective by Jong Won Lee, Min Whan Jung, Min Whan Jung

“…Based on these findings, we propose that the CA3 region of the hippocampus generates diverse activity patterns, while the CA1 region evaluates and reinforces those patterns most likely to maximize rewards. …”
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Design Method for Low-Ice-Class Propellers Based on Multi-Objective Optimization by Chenxu Gu, Kang Han, Kaiqiang Weng, Chao Wang, Chunhui Wang

“…The study also addresses key aspects such as geometric parameterization, the selection of optimization variables, the implementation of optimization algorithms, and the balance of multi-objective trade-offs. …”
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Analyzing key users’ behavior trends in volunteer-based networks by Nofar Piterman, Tamar Makov, Michael Fire

“…We introduce two innovative algorithms: the first outlines the evolution of volunteers’ behavior patterns over time, while the second employs machine learning techniques to forecast their future behavior, including whether they will remain active donors or become mainly recipients, and vice-versa. …”
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Prediksi Penggunaan Obat Peserta Jaminan Kesehatan Nasional Menggunakan Algoritma Naïve Bayes Classifier by Tugiman, Lily Damayanti, Alexius Hendra Gunawan, Samuel Ryon Elkana

“…A distinctive feature of this method is that it uses a very strong assumption of the independence of each event. While software testing uses the User Acceptance Test (UAT) model. …”
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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…This paper proposed a hybrid filter-wrapper algorithm for feature selection based on an index of important features used in the pavement classification task; it takes advantage of two pure methods: the fast speed of the filter and the efficiency of the wrapper method. …”
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