Answer Distillation Network With Bi-Text-Image Attention for Medical Visual Question Answering by Hongfang Gong, Li Li

“…Med-VQA, as a classification task, is typically more challenging for algorithms to predict answers to open-ended questions than to closed-ended questions due to the larger number of answer categories for the former. …”
Get full text

Robust fully distributed file caching for delay-tolerant networks: A reward-based incentive mechanism by Sidi Ahmed Ezzahidi, Essaid Sabir, Sara Koulali, El-Houssine Bouyakhf

“…Then, we propose three fully distributed algorithms to ensure convergence to the Nash equilibria (for both pure equilibrium and mixed equilibrium). …”
Get full text

XXIX Expert Advisory Board of the Russian Glaucoma Society, the XII meeting of the International Expert Advisory Board on glaucoma issues by A.V. Seleznev

“…Besides, a separate vector was the unification of these approaches and the development of uniform algorithms by the World Glaucoma Association.<br> <br> <b>About the author:</b><br> Aleksei V. …”
Get full text

Refining the prediction of user satisfaction on chat-based AI applications with unsupervised filtering of rating text inconsistencies by Hae Sun Jung, Jang Hyun Kim, Haein Lee

“…Subsequently, the authors conduct supervised sentiment analysis using various machine learning and deep learning algorithms. The experimental results confirm the effectiveness of the proposed approach showing improvement in prediction accuracy with cost efficiency. …”
Get full text

The Video Manipulation Effect (VME): A quantification of the possible impact that the ordering of YouTube videos might have on opinions and voting preferences. by Robert Epstein, Alex Flores

“…In 2018, a YouTube official revealed that 70% of the time people spend watching videos on the site, they are watching content that has been suggested by the company's recommender algorithms. If the findings in the present study largely apply to YouTube, this popular video platform might have unprecedented power to impact thinking and behavior worldwide.…”
Get full text

Investigating the Relationship Between Drought Parameters and Food Security Using Data Mining Methods (Case study: Alborz Province) by Mohammad Ansari Ghojghar

“…The results showed that in Taleghan and Karaj, the goodness of fit criteria of R2, RMSE and MAE of Spearman, ANN, ANFIS and M5 methods were from 0.752 to 0.736, 0.242 to 0.217, 0.107 to 114 respectively. 0.847 to 0.837, 0.209 to 0.253, and 0.107 to 0.111 are variable. Also, among the algorithms used, the M5 decision tree method was the best model for measuring the correlation between drought variables and food security...…”
Get full text

Handling Multiple-Fuel Options in Economic Dispatch of Thermal Power Plants Through a Tight Model Applying Indicator Variables by Hossein Sharifzadeh

“…Furthermore, the proposed approach generally outperforms earlier algorithms in terms of solution quality and robustness. …”
Get full text

Secret sharing in a special linear group by V. I. Yanchevskiĭ, I. A. Havarushka, G. V. Matveev

“…A rigorous mathematical justification is given for the correctness of the algorithms for generating partial secrets and restoring the main secret in the special linear group over the ring of integers. …”
Get full text

A System of Remote Patients’ Monitoring and Alerting Using the Machine Learning Technique by M. Dhinakaran, Khongdet Phasinam, Joel Alanya-Beltran, Kingshuk Srivastava, D. Vijendra Babu, Sitesh Kumar Singh

“…The proposed methodology makes use of different machine learning algorithms along with cloud computing for continuous data storage. …”
Get full text

Shape Restoration by Active Self-Assembly by D. Arbuckle, A. A. G. Requicha

“…Simulations presented here show that swarms of such robots organize themselves to achieve shape restoration by using distributed algorithms. This is one more example of an interesting geometric problem that can be solved by the Active Self-Assembly paradigm introduced in previous papers by the authors.…”
Get full text

QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP AND MOLECULAR DOCKING STUDIES OF HYDROXAMIC ACID DERIVATIVES AS NOVEL CLASS INHIBITORS AGAINST HELICOBACTER PYLORI UREASE by Ibrahim Tijjani Ibrahim, Adamu Uzairu, Balarabe Sagagi

“…Relevant molecular descriptors were selected by Genetic Function Algorithms (GFA). The best model obtained was given a distinct validated, good and robust statistical parameters which include; square correlation coefficient R2 value of (0.9989), adjusted determination coefficient, R2adj value of (0.9984), Leave one out cross validation determination coefficient Q2 value of (0.9948) and external validation as predicted determination coefficient R2 value of(0.8409). …”
Get full text

Recent Research Progress on Ground-to-Air Vision-Based Anti-UAV Detection and Tracking Methodologies: A Review by Arowa Yasmeen, Ovidiu Daescu

“…Our study examines recent UAV detection and tracking algorithms, outlining their operational principles, advantages, and disadvantages. …”
Get full text

A Model-Driven Realization of AUV Controllers Based on the MDA/MBSE Approach by Ngo Van Hien, Van-Thuan Truong, Ngoc-Tam Bui

“…This paper introduces a model-driven control realization, which is based on the systems engineering concepts of the model-driven architecture (MDA)/model-based systems engineering (MBSE) approach combined with the real-time UML/SysML, extended/unscented Kalman filter (EKF/UKF) algorithms, and hybrid automata, in order to conveniently deploy controllers of autonomous underwater vehicles (AUVs). …”
Get full text

Motor control method using single-sensor phase current reconstruction by Yin Lu, Yuntian Huang, Hao Guo

“…Simultaneously, optimization algorithms like neural networks are employed to learn from historical data to predict and estimate the current values of the three phases. …”
Get full text

Improving the resolution of solar energy potential maps derived from global DSMs for rooftop solar panel placement using deep learning by Maryam Hosseini, Hossein Bagheri

“…Subsequently, deep learning algorithms were trained to improve the resolution of the LiDAR-derived ASM. …”
Get full text

Deciphering the Immune Subtypes and Signature Genes: A Novel Approach Towards Diagnosing and Prognosticating Severe Asthma Through Interpretable Machine Learning by Yue Hu, Yating Lin, Bo Peng, Chunyan Xiang, Wei Tang

“…We employ single-sample gene set enrichment analysis (ssGSEA) and Least Absolute Shrinkage and Selection Operator (LASSO) algorithms to identify differentially expressed immune cells and utilize machine learning techniques, including Extreme Gradient Boosting (XGBoost) and random forest, to predict severe asthma outcomes and identify key genes associated with immune cells. …”
Get full text

Predicting Changes of the Cultivation Areas for Astamaran and Berhi Cultivars in Iran in the 21st Century by Maryam Afzali, javad khoshhal dastjerdi, Aziz Torahi

“…Global warming in the last century has led planners to design pre-awareness programs and algorithms due to future climatic conditions in order to choose long-lived durable plants that can survive in future environmental conditions and have good economic yield. …”
Get full text

Minimizing Delay and Power Consumption at the Edge by Erol Gelenbe

“…Thus, substantial research has been conducted to identify optimum task allocation schemes in this context using non-linear optimization, machine learning, and market-based algorithms. Prior work has mainly focused on two methodologies: (i) formulating non-linear optimizations that lead to NP-hard problems, which are processed via heuristics, and (ii) using AI-based formulations, such as reinforcement learning, that are then tested with simulations. …”
Get full text

Optimal Robust Time-Domain Feature-Based Bearing Fault and Stator Fault Diagnosis by G. Geetha, P. Geethanjali

“…The deep learning techniques that automatically extract features and perform classification have algorithmic complexity. In this work, the authors address these challenges by: 1) selecting and ensembling optimal time-domain features that are capable of identifying motor faults using current signals of the permanent magnet synchronous motor (PMSM) in bearing; and 2) investigating the feature ensemble constituting optimal features for robust fault diagnosis in the PMSM bearing as well as the stator and bearing of squirrel cage induction motor (SCIM) for various conditions. …”
Get full text

Flow and Transport in Tight and Shale Formations: A Review by Amgad Salama, Mohamed F. El Amin, Kundan Kumar, Shuyu Sun

“…Each scale has its own tools and limitations that may not, probably, be suitable at other scales. Multiscale algorithms that effectively couple simulations among various scales of porous media are therefore important. …”
Get full text