Ali Moeini
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View article: A Pipeline to Construct Breast Cancer Knowledge Graph from Scientific Literature (Preprint)
A Pipeline to Construct Breast Cancer Knowledge Graph from Scientific Literature (Preprint) Open
BACKGROUND The rapid growth of biomedical information has intensified the need for effective knowledge-management techniques. In this context, information organization is critical because biomedical texts contain numerous relations among …
View article: Safe In-Context Reinforcement Learning
Safe In-Context Reinforcement Learning Open
In-context reinforcement learning (ICRL) is an emerging RL paradigm where the agent, after some pretraining procedure, is able to adapt to out-of-distribution test tasks without any parameter updates. The agent achieves this by continually…
View article: Exploring Novel Graphs with Diverse Properties for Real-World Applications
Exploring Novel Graphs with Diverse Properties for Real-World Applications Open
View article: A Survey of In-Context Reinforcement Learning
A Survey of In-Context Reinforcement Learning Open
Reinforcement learning (RL) agents typically optimize their policies by performing expensive backward passes to update their network parameters. However, some agents can solve new tasks without updating any parameters by simply conditionin…
View article: Enhancing Aspect-based Sentiment Analysis with ParsBERT in Persian Language
Enhancing Aspect-based Sentiment Analysis with ParsBERT in Persian Language Open
In the era of pervasive internet use and the dominance of social networks, researchers face significant challenges in Persian text mining including the scarcity of adequate datasets in Persian and the inefficiency of existing language mode…
View article: A post-quantum lattice-based lightweight anonymous authentication scheme for IoT
A post-quantum lattice-based lightweight anonymous authentication scheme for IoT Open
The Internet of Things (IoT) comprises a complex network of smart objects that collect and exchange data with each other via the public Internet. Radio-frequency identification (RFID) technology is currently one of the most important IoT t…
View article: Machine Learning‐Driven Band Gap Prediction/Classification and Feature Importance Analysis of Inorganic Perovskites
Machine Learning‐Driven Band Gap Prediction/Classification and Feature Importance Analysis of Inorganic Perovskites Open
Perovskites are a class of materials, known for their diverse structural, electronic, and optical properties. Band gap in perovskites is crucial in determining their suitability for applications such as solar cells, light‐emitting diodes, …
View article: Machine learning-enhanced band gaps prediction for low-symmetry double and layered perovskites
Machine learning-enhanced band gaps prediction for low-symmetry double and layered perovskites Open
View article: Tightness of Harary Graphs
Tightness of Harary Graphs Open
In the design of real-world networks, researchers evaluate various structural parameters to assess vulnerability, including connectivity, toughness, and tenacity. Recently, the tightness metric has emerged as a potentially superior vulnera…
View article: Tightness of Harary Graphs
Tightness of Harary Graphs Open
In the design of real-world networks, researchers evaluate various structural parameters to assess vulnerability, including connectivity, toughness, and tenacity. Recently, the tightness metric has emerged as a potentially superior vulnera…
View article: Introducing new Link Prediction Measures and an Evaluation Metric
Introducing new Link Prediction Measures and an Evaluation Metric Open
Link prediction plays a critical role in network analysis as it tackles the task of predicting missing or future connections within a given network. A wide array of link prediction measures has been proposed to estimate the likelihood of l…
View article: The Effectiveness of Metaverse in e-Learning
The Effectiveness of Metaverse in e-Learning Open
On using a 3D model to teach students a topic in astronomy, feedback was evaluated via a questionnaire. Analysis of students' responses to the questions revealed that user interface had a significant impact on their attitudes, which i…
View article: Software reliability prediction: A machine learning and approximation Bayesian inference approach
Software reliability prediction: A machine learning and approximation Bayesian inference approach Open
Reliability growth models are commonly categorized into two primary groups: parametric and non‐parametric models. Parametric models, known as Software Reliability Growth Models (SRGM) rely on a set of hypotheses that can potentially affect…
View article: Survey on Applications of Graph Theory in Information Retrieval
Survey on Applications of Graph Theory in Information Retrieval Open
Survey on Applications of Graph Theory in Information Retrieval
View article: Classification of Potential Breast/Colorectal Cancer Cases Using Machine Learning Methods
Classification of Potential Breast/Colorectal Cancer Cases Using Machine Learning Methods Open
Background: The algorithmic classification of infected and healthy individuals by gene expression has been a topic of interest to researchers in numerous domains, including cancer. Several studies have presented numerous solutions, such as…
View article: Parallel molecular alteration between Alzheimer’s disease and major depressive disorder in the human brain dorsolateral prefrontal cortex: an insight from gene expression and methylation profile analyses
Parallel molecular alteration between Alzheimer’s disease and major depressive disorder in the human brain dorsolateral prefrontal cortex: an insight from gene expression and methylation profile analyses Open
Alzheimer's disease (AD) and major depressive disorder (MDD) are comorbid neuropsychiatric disorders that are among the leading causes of long-term disability worldwide. Recent research has indicated the existence of parallel molecular mec…
View article: Survey on the Applications of the Graph Theory in the Information Retrieval
Survey on the Applications of the Graph Theory in the Information Retrieval Open
نظریه گراف بواسطه توانمندی در مدلسازی روابط پیچیده بین عناصر در مسائل مختلف، بصورت گسترده مورد استفاده قرار گرفته است. از سوی دیگر، بازیابی اطلاعات یعنی استخراج اطلاعات مورد نیاز کاربر، به عنوان یکی از مسائل مهم در دنیای الگوریتم و محاسبات…
View article: Software Reliability Prediction: A Machine Learning and Approximation Bayesian Inference Approach
Software Reliability Prediction: A Machine Learning and Approximation Bayesian Inference Approach Open
View article: LSTM Encoder-Decoder Dropout Model in Software Reliability Prediction
LSTM Encoder-Decoder Dropout Model in Software Reliability Prediction Open
Numerous methods have been introduced to predict the reliability of software. In general, these methods can be divided into two main categories, namely parametric (e.g. software reliability growth models) and non-parametric (e.g. neural ne…
View article: D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning
D2RLIR : an improved and diversified ranking function in interactive recommendation systems based on deep reinforcement learning Open
Recently, interactive recommendation systems based on reinforcement learning have been attended by researchers due to the consider recommendation procedure as a dynamic process and update the recommendation model based on immediate user fe…
View article: D2RLIR : an improved and diversified ranking function in interactive\n recommendation systems based on deep reinforcement learning
D2RLIR : an improved and diversified ranking function in interactive\n recommendation systems based on deep reinforcement learning Open
Recently, interactive recommendation systems based on reinforcement learning\nhave been attended by researchers due to the consider recommendation procedure\nas a dynamic process and update the recommendation model based on immediate\nuser…
View article: Designing a semantic intelligence-based planning framework in the ministry of science, research and technology with two macro and detailed approaches
Designing a semantic intelligence-based planning framework in the ministry of science, research and technology with two macro and detailed approaches Open
Semantic data management in organizations requires careful design of the appropriate semantic planning model that can best drive the organization to its goals. Therefore, designing a semantic framework to make decisions with minimum error …
View article: Designing a semantic intelligence-based planning framework in the ministry of science, research and technology with two macro and detailed approaches
Designing a semantic intelligence-based planning framework in the ministry of science, research and technology with two macro and detailed approaches Open
Semantic data management in organizations requires careful design of the appropriate semantic planning model that can best drive the organization to its goals. Therefore, designing a semantic framework to make decisions with minimum error …
View article: Design Software Failure Mode and Effect Analysis using Fuzzy TOPSIS Based on Fuzzy Entropy
Design Software Failure Mode and Effect Analysis using Fuzzy TOPSIS Based on Fuzzy Entropy Open
One of the key pillars of any operating system is its proper software performance. Software failure can have dangerous effects and consequences and can lead to adverse and undesirable events in the design or use phases. The goal of this st…
View article: Estimating runtime of a job in Hadoop MapReduce
Estimating runtime of a job in Hadoop MapReduce Open
View article: A Hybrid Approach to Enhance Pure Collaborative Filtering based on Content Feature Relationship
A Hybrid Approach to Enhance Pure Collaborative Filtering based on Content Feature Relationship Open
Recommendation systems get expanding significance because of their applications in both the scholarly community and industry. With the development of additional data sources and methods of extracting new information other than the rating h…
View article: A survey of Cloud-based Radio-frequency Identification Authentication Protocols and Improvements to One of the Latest Proposed Protocols
A survey of Cloud-based Radio-frequency Identification Authentication Protocols and Improvements to One of the Latest Proposed Protocols Open
The development of IoT and cloud data storage has enabled several objects to access the internet through radio-frequency identification (RFID) systems.Currently, the use of the cloud as a backend server is considered as a viable and cost-e…
View article: Estimating runtime of a job in Hadoop MapReduce
Estimating runtime of a job in Hadoop MapReduce Open
Hadoop MapReduce is a framework to process vast amounts of data in the cluster of machines in a reliable and fault-tolerant manner. Since being aware of the runtime of a job is crucial to subsequent decisions of this platform and being bet…
View article: Estimating runtime of a job in Hadoop MapReduce
Estimating runtime of a job in Hadoop MapReduce Open
Hadoop MapReduce is a framework to process vast amounts of data in the cluster of machines in a reliable and fault-tolerant manner. To better management of this framework, estimating the runtime of a job is an important but challenging pro…
View article: An exponential similarity measure for collaborative filtering
An exponential similarity measure for collaborative filtering Open