Academic Articles & Research Papers

Assembly Function Recognition in Embedded Systems as an Optimization Problem

Many different aspects of software system development and verification rely on precise function identification in binary code. Recognition of the source Assembly functions in embedded systems is one of the fundamental challenges in binary p...

Proposing New Data Whitening Method through Application of LSTM Method for Fault Condition Prediction in Bearing Data

In the context of big data, data preprocessing, especially data whitening, plays a pivotal role in improving the effectiveness of AI models. While traditional whitening methods suffer from severe computational bottlenecks, arising from the ...

A computational tool for conceptual design and optimization of planetary rovers

The design process of a Mars rover is driven by multiple design constraints, namely overall mass, power consumption and volume (dimensions). Various systems, such as mobility, manipulation, handling, power, thermal, communication, navigatio...

FEATURES using reversible logic operations IN MODELING IRREVERSIBLE COMPUTING on the reversibly COMPUTER

Information can be recorded in the quantum state and are transmitted via the physical channel. The theory of quantum coding and information theory quantum computing related. In any information system ( classical or quantum) will always cont...

Modeling Semantic Relations Expressed by Prepositions

Natural Language Processing in Psychiatry

The potential benefit of artificial intelligence (AI) technology as a tool of psychiatry has not been well defined. In this essay, the technology of natural language processing and its position with regard to the two main schools of AI is c...

Semantic Alignment in Disciplinary Tutoring System: Leveraging Sentence Transformer Technology

In this work, we present a disciplinary e-tutoring system that integrates ONTO-TDM, an ontology designed for teaching domain modeling, with advanced transformer technology. Our primary objective is to enhance semantic similarity tasks withi...

Machine Unlearning: A Perspective, Taxonomy, and Benchmark Evaluation

Machine Learning (ML) models trained on large-scale datasets learn useful predictive patterns, but they may also memorize undesired information, leading to risks such as information leakage, bias, copyright violations, and privacy attacks. ...

Sentiment Analysis and Topic Modeling of Indonesian Public Conversation about COVID-19 Epidemics on Twitter

The World Health Organization (WHO) declared the COVID-19 outbreak has resulted in more than six million confirmed cases and more than 371,000 deaths globally on June 1, 2020. The incident sparked a flood of scientific research to help soci...

Natural Language Processing and Information Retrieval

Natural Language Processing and Information Retrieval is a textbook designed to meet the requirements of engineering students pursuing undergraduate and postgraduate programs in computer science and information technology. The book attempts...

Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing

Pretraining large neural language models, such as BERT, has led to impressive gains on many natural language processing (NLP) tasks. However, most pretraining efforts focus on general domain corpora, such as newswire and Web. A prevailing a...

Topic Modeling and Content Analysis of Chinese Medical Device Policies Using BERTopic.

Ensembles machine learning for short duration rainfall intensity forecasting

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

Comparative Study of CNN and RNN for Natural Language Processing

Deep neural networks (DNN) have revolutionized the field of natural language processing (NLP). Convolutional neural network (CNN) and recurrent neural network (RNN), the two main types of DNN architectures, are widely explored to handle var...

Methods for Analyzing the Contents of Social Media for Health Care: Scoping Review

BackgroundGiven the rapid development of social media, effective extraction and analysis of the contents of social media for health care have attracted widespread attention from health care providers. As far as we know, most of the reviews ...

Paradigm Shift in Natural Language Processing

Abstract In the era of deep learning, modeling for most natural language processing (NLP) tasks has converged into several mainstream paradigms. For example, we usually adopt the sequence labeling paradigm to solve a bundle of tasks such as...

GBsim: A Robust GCN-BERT Approach for Cross-Architecture Binary Code Similarity Analysis

Recent advances in graph neural networks have transformed structural pattern learning in domains ranging from social network analysis to biomolecular modeling. Nevertheless, practical deployments in mission-critical scenarios such as binary...

Natural Language Processing

Understanding and processing human language has always been a complicated task in computational theory. Natural language processing, a combination of artificial intelligence and computational linguistics, employs computational techniques to...

A Model-Driven Approach Employing DSL and Generation Templates to Accelerate the Development of Conversational Agents for Smart Tourism

Conversational agents are intelligent, ubiquitous software applications widely used across various sectors, such as commerce, tourism, and more. Their key benefits include automating tasks, improving customer service, and ensuring service a...

A maximum entropy approach to natural language processing

The concept of maximum entropy can be traced back along multiple threads to Biblical times. Only recently, however, have computers become powerful enough to permit the widescale application of this concept to real world problems in statisti...