SAGE2Splice: unmapped SAGE tags reveal novel splice junctions. by Byron Yu-Lin Kuo, Ying Chen, Slavita Bohacec, Ojvind Johansson, Wyeth W Wasserman, Elizabeth M Simpson

“…To test this hypothesis, we have developed an algorithm, SAGE2Splice, to efficiently map SAGE tags to potential splice junctions in a genome. …”
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A Model of Gamification by Combining and Motivating E-Learners and Filtering Jobs for Candidates by Sherin Eliyas, Ranjana P

“…This enables us to gather information from the candidates and make accurate predictions about the jobs that might suit them. This is also durable in the sense that any missing data about the candidate does not affect the algorithm as a whole as it is capable of making assumptions regarding the missing data based on similar data already stored in the database. …”
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The implementation of random survival forests in conflict management data: An examination of power sharing and third party mediation in post-conflict countries. by Andrew B Whetten, John R Stevens, Damon Cann

“…Further, the RSF, a previously under-used method for analyzing political science time-to event data, provides a novel approach for ranking of peace agreement criteria importance in predicting peace agreement duration. Our findings demonstrate a scenario exhibiting the interpretability and performance of RSF for political science time-to-event data. …”
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Landing attitude analysis and control of bouncing robots by WU Zhe, ZHOU Zupeng, YANG Quan

“…Finally, a prototype was built to verify the feasibility of using the momentum wheel to change the attitude of the bouncing robot.ResultsThe designed attitude control mechanism based on three orthogonal momentum wheels combined with the integral sliding mode control algorithm can effectively control the attitude of the robot after bouncing, and the proposed robot landing stability criterion can effectively predict the stability of the robot through the current robot state.…”
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Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

“…In this paper, we propose an engagement recognition system that detects student engagement using EEG signals by integrating levels of valence and arousal with the Russel 2D circumplex model using deep learning algorithm. The public DEAP dataset was used for training the model to predict valence and arousal values. …”
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DNFE: Directed network flow entropy for detecting tipping points during biological processes. by Xueqing Peng, Rui Qiao, Peiluan Li, Luonan Chen

“…Furthermore, the numerical simulations for 100-node and 1000-node gene regulatory networks illustrate the method's application for large-scale data. The DNFE method predicts active transcription factors, and further identified "dark genes", which are usually overlooked with traditional methods.…”
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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

“…The results show that the maximum error between the calculation results of the developed numerical model and the experimental results is 3.87%, and the maximum error between the predicted values of the trained surrogate model and the true values is 0.15%. …”
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X-FuseRLSTM: A Cross-Domain Explainable Intrusion Detection Framework in IoT Using the Attention-Guided Dual-Path Feature Fusion and Residual LSTM by Adel Alabbadi, Fuad Bajaber

“…The model effectively incorporates both spatial and temporal correlations in network traffic data, which improves its detection capability. The model predictions are explained using the XAI techniques. …”
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Hyperspectral Imaging Combined with Deep Learning for the Early Detection of Strawberry Leaf Gray Mold Disease by Yunmeng Ou, Jingyi Yan, Zhiyan Liang, Baohua Zhang

“…Overall, the fused feature-based model can reduce the dimensionality of the classification data and effectively improve the predicting accuracy and precision of the classification algorithm.…”
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In-silico and in-vitro morphometric analysis of intestinal organoids. by Sandra Montes-Olivas, Danny Legge, Abbie Lund, Alexander G Fletcher, Ann C Williams, Lucia Marucci, Martin Homer

“…Developing tools to assess and predict the behaviour of these systems may produce a more robust and standardised biological model to perform accurate clinical studies. …”
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Artificial Intelligence in Identifying Patients With Undiagnosed Nonalcoholic Steatohepatitis by Onur Baser, Gabriela Samayoa, Nehir Yapar, Erdem Baser

“… # Conclusions Utilization of machine learning to predict NASH allows for wider recognition, timely intervention, and targeted treatments to improve or mitigate disease progression and could be used as an initial screening tool.…”
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Evaluation of the impact of COVID-19 on hepatitis B in Henan Province and its epidemic trend based on Bayesian structured time series model by Xinxiao Li, Yanyan Li, Shushuo Xu, Penghao Wang, Meng Hu, Haibin Li, Yongbin Wang

“…To assess how well the BSTS algorithm performs predictions, we split the observations into various training and testing ranges. …”
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Artificial intelligence in personalized cardiology treatment by Abbas Mohammadi, Sheida Shokohyar

“…Personalized medicine customizes interventions according to individual characteristics, with artificial intelligence (AI) playing a key role in analyzing complex data to improve diagnostic accuracy, predict outcomes, and optimize therapies. AI can identify patterns in imaging and biomarkers, facilitating the earlier detection of medical conditions. …”
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A Novel Mechanism for Fire Detection in Subway Transportation Systems Based on Wireless Sensor Networks by Zhen-Jiang Zhang, Jun-Song Fu, Hua-Pei Chiang, Yueh-Min Huang

“…The mechanism uses the quantity information acquired from the data and also considers the distribution information of the data in order to predict the occurrence of fire incidents. The simulation results show that fire incidents can be detected fast and efficiently.…”
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Sequential Multidimensional Scaling with Kalman Filtering for Location Tracking by Lan Anh Trinh, Nguyen Duc Thang, Dang Viet Hung, Tran Cong Hung

“…In this paper, we propose a solution to attenuate noise effects to MDS by combining MDS with a Kalman filter. A model is built to predict the noise distribution with regard to additive noises to the distance measurements following the Gaussian distribution. …”
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Swarm Control with RRT-APF Planning and FNN Task Allocation Tested on Mobile Differential Platform by Michal Lajčiak, Ján Vachálek

“…A feedforward neural network was developed to assign tasks to swarm agents in real time by predicting a suitability score. For centralized swarm planning, a hybrid algorithm combining Rapidly Exploring Random Tree (RRT) and Artificial Potential Field (APF) planners was implemented, incorporating a Multi-Agent Pathfinding (MAPF) solution to resolve simultaneous collisions at intersections. …”
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Application of Monte Carlo Method for Gamma ray Attenuation Properties of Lead Zinc Borate Glasses by Urkiye Akar Tarım, Orhan Gürler

“…Thesimulation results have been verified with predictions from the XCOM program inthe studied energy region from 1 keV to 2000 keV and experimental results.Thus, this verification indicated that this research method can be followed todetermine the interaction and attenuation of gamma rays with the severalenergies in different materials. …”
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A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

“…A learning automaton is used to feed a neural network with the ability to predict a student’s ability based on their response history. …”
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Impact of Climate Change on the Distribution of <i>Cinnamomum malabatrum</i> (Laurales—Lauraceae), a Culturally and Ecologically Important Species of Malabar, Western Ghats, India... by Mukesh Lal Das, Sarat Chandran, Sreenath Subrahmanyam

“…The predicted range shifts and contraction of suitable habitats for the species indicate significant challenges ahead, especially in the Malabar midlands and coastal plains—areas of high endemicity. …”
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Optimisation of material composition in functionally graded plates using a structure-tuned deep neural network by Ryoichi Chiba, Takuya Kishida, Ryoto Seki, Seiya Sato

“…A fully-connected NN, configured with an open-source Bayesian optimisation framework, is employed to predict the maximum in-plane thermal stress for various combinations of design variables. …”
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