Domain-Invariant Label Propagation With Adaptive Graph Regularization by Yanning Zhang, Jianwen Tao, Liangda Yan

“…An effective optimization algorithm is proposed for addressing the optimization problem of DILO. …”
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Sentence Embedding Based Semantic Clustering Approach for Discussion Thread Summarization by Atif Khan, Qaiser Shah, M. Irfan Uddin, Fasee Ullah, Abdullah Alharbi, Hashem Alyami, Muhammad Adnan Gul

“…Next, K-medoid clustering algorithm is applied to group semantically similar reply sentences in order to reduce the overlapping reply sentences. …”
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Multiple Parameters Determination Method of Hardening Soil Model Based on Particle Swarm Optimization by Jingfeng Xiao, Qunwei Wang, Qianhui Zhang, Yunpeng Hei, Youliang Zhang

“…The results demonstrate a high degree of consistency between the experimental curves and the five parameter combinations obtained through the PSO algorithm, with an error rate not exceeding 8.2%. Moreover, the optimized curves exhibit closer alignment with theoretical expectations. …”
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Using machine learning-based models for personality recognition by Fatemeh Mohades Deilami, Hossein Sadr, Mozhdeh Nazari

“…Owing to the fact that various filter sizes in CNN may influence its performance, we decided to combine CNN with AdaBoost, a classical ensemble algorithm, to consider the possibility of using the contribution of various filter lengths and gasp their potential in the final classification via combining various classifiers with respective filter size using AdaBoost. …”
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Evaluating the predictive potential of RSM and ANN models in treatment of greywater-syrup mixture using Ekowe clay-PEM microbial fuel cell by Livinus A. Obasi, Cornelius O. Nevo

“…A 24 central composite design and a three-layered (4:n:1) feedforward ANN architecture trained by a backpropagation algorithm were used to study and predict the MFC process performance criteria. …”
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Comparison Between Convolutional Neural Network CNN and SVM in Skin Cancer Images Recognition by Zaid Ghazi Hadi, Ahmed R. Ajel, Ayad Q. Al-Dujaili

“…Which is a supervised learning algorithm and it is used for classification of data for the different classes based on a separating hyperplane. …”
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Determining Planetary Boundary Layer Height by Micro-pulse Lidar with Validation by UAV Measurements by Yueh-Chen Wang, Sheng-Hsiang Wang, Jasper R. Lewis, Shuenn-Chin Chang, Stephen M. Griffith

“…Furthermore, the Haar wavelet and the Hybrid image processing can detect the PBL development comparably well, but both methods are dependent on their initial conditions and optimized algorithm settings. In addition, the accompanying UAV observations are conclusively shown to have a high degree of efficacy for validating the lidar data. …”
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Problems of legal regulation of start-ups in Ukraine by I. V. Lysenko, А. M. Lysenko, L. V. Perevalova

“…The article is devoted to the study of the theoretical and legal nature of start-ups, their features, and the legal algorithm of their creation, operation, and termination of activities, with due regard to the existing legislative provisions and doctrinal developments. …”
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Accurate inversion of chlorophyll content based on PROSPECT-LSROGF-BAS-BP method by Shengfan Zhu, Jin Zhang, Dan Wang, Rui Ding

“…Next, to improve the retrieval accuracy of traditional BP neural networks for chlorophyll content, the Beetle Antennae Search (BAS) algorithm is used to optimize the weights and thresholds of the BP neural network, forming the BAS-BP model. …”
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A Method for Tomato Ripeness Recognition and Detection Based on an Improved YOLOv8 Model by Zhanshuo Yang, Yaxian Li, Qiyu Han, Haoming Wang, Chunjiang Li, Zhandong Wu

“…Thus, a deep learning algorithm for tomato ripeness detection based on an improved YOLOv8n is proposed in this study. …”
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Depression Recognition Using Daily Wearable-Derived Physiological Data by Xinyu Shui, Hao Xu, Shuping Tan, Dan Zhang

“…Utilizing a Random Forest algorithm, we distinguished depressive and non-depressive individuals with varying classification accuracies on data aggregated over 6 h, 2 h, 30 min, and 5 min segments, as 90.0%, 84.7%, 80.1%, and 76.0%, respectively. …”
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Least Square Estimation-Based Different Fast Fading Channel Models in MIMO-OFDM Systems by Walaa Hussein, Kamil Audah, N. K. Noordin, Habib Kraiem, Aymen Flah, Mohd Fadlee, Alyani Ismail

“…To address this issue, an efficient dataset is utilized, employing the least square (LS) algorithm for minimization. OFDM is a commonly and widely used modulation method in communication systems utilized to specifically combat resonance fading in wireless channels. …”
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Energy-Efficient Aerial STAR-RIS-Aided Computing Offloading and Content Caching for Wireless Sensor Networks by Xiaoping Yang, Quanzeng Wang, Bin Yang, Xiaofang Cao

“…We propose a deep reinforcement learning (DRL)–successive convex approximation (SCA) combined algorithm to iteratively achieve near-optimal solutions with low complexity. …”
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Analysis of the Outer Contour Characteristics of Roadway Forming under the Influence of Cutting Head Vibration by Zhixiang Liu, Shuai Wang, Miao Xie, Chunxue Xie

“…The vibration of the cutting head when cutting coal and rock will have a great influence on the outer profile of the roadway, which cannot be ignored in the research of accurate autonomous cutting control algorithm of roadheader. The research results of this paper can provide a basis for the optimization of cutting parameters and high-precision forming control method of roadheader.…”
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Research on network risk assessment based on attack graph of expected benefits-rate by Wenfu LIU, Jianmin PANG, Xin ZHOU, Nan LI, Feng YUE

“…As Internet applications and services become more and more extensive, the endless network attacks lead to great risks and challenges to the security of information systems.As a model-based network security risk analysis technology, attack graph is helpful to find the vulnerability between network nodes and the harm of being attacked.It has been proved to be an effective method to find and prevent network security risks.Attack graph is mainly divided into state-based attack graph and attribute-based attack graph.Due to the problem of state explosion in state-based attack graph, most researchers prefer the attribute-based attack graph for network risk assessment.In view of the existing researches on attribute-based attack graph, they excessively rely on the vulnerability of network nodes and the essential attributes of atomic attack.However, they ignore that rational attackers usually choose specific attack paths by maximizing attack benefits.Then, a network risk assessment framework and a quantification method of attack benefits-rate based on expected benefits-rate attack graph were proposed.The network risk assessment framework took the open vulnerability resource database, the new vulnerabilities found by the vulnerability mining system and the big data related to network attack and defense as the basic data source.The network risk assessment framework also took the open source big data platform as the analysis tool to mine and calculate the elements related to attack cost and attack benefit.Using the concepts of cost, benefit and benefit-rate in economics, the calculation model of expected benefit-rate of atomic attack was constructed.By constructing the attribute-based attack graph of the target network, the expected benefit-rate of atomic attack on the attack path was calculated, and the expected benefit-rate list of all possible attack paths was generated.Furthermore, taking the expected goal as the starting point, the search was carried out according to the specific optimization strategy (backtracking method, greedy algorithm, dynamic programming).And the complete attack path with the maximum benefit-rate was obtained, which provided the basis for network risk assessment.The simulation results show the effectiveness and rationality of the proposed expected benefit-rate attack graph network risk assessment method, which can provide support for discovering and preventing network security problems.…”
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Predicting patients’ sentiments about medications using artificial intelligence techniques by Amir Sorayaie Azar, Samin Babaei Rikan, Amin Naemi, Jamshid Bagherzadeh Mohasefi, Uffe Kock Wiil

“…Three scenarios were considered for classification, including two, three, and ten classes. The Word2Vec algorithm and pre-trained word embeddings, including the general and clinical domains, were utilized in model development. …”
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Evaluation of laboratory findings indicating pancreatitis in healthy lean, obese, and diabetic cats by Freja K. Jørgensen, Charlotte R. Bjornvad, Birgit Krabbe, Stinna Nybroe, Ida N. Kieler

“…Fisher's exact test assessed the proportions of cats with fPLI and fTLI indicative of pancreatitis, and hypocobalaminemia. A random forest algorithm identified explanatory variables for cats having fPLI levels indicative of pancreatitis. …”
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The prediction model of academic achievement based on cardiorespiratory fitness and BMI status for ninth-grade students by Viktor Bielik, Vladimír Nosáľ, Libuša Nechalová, Milan Špánik, Katarína Žilková, Marian Grendar

“…The results from the Random Forest Regression (RFR) machine learning algorithm suggest that adolescents who meet the international CRF and BMI criterion-referenced standards have a higher probability of getting a higher academic achievement score than unfit students with overweight or obesity. …”
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Optimized radiofrequency shimming using low-heating B1+-mapping in the presence of deep brain stimulation implants: Proof of concept. by Maryam Arianpouya, Benson Yang, Fred Tam, Clare E McElcheran, Simon J Graham

“…A two-step optimization algorithm is proposed and examined for a cylindrical phantom with an implanted wire to enable 1) robust B1+ mapping with low localized heating; and 2) robust RF shimming PTX with low localized heating and good B1+ homogeneity over a large imaging volume. …”
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Evaluating 28-Days Performance of Rice Husk Ash Green Concrete under Compression Gleaned from Neural Networks by Sharanjit Singh, Harish Chandra Arora, Aman Kumar, Nishant Raj Kapoor, Kennedy C. Onyelowe, Krishna Kumar, Hardeep Singh Rai

“…In this study, a total of 407 datasets are used to develop an ML-based model by using the ANN algorithm to predict the CS of concrete containing RHA. …”
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