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Studia Universitatis Babes-Bolyai: Series Informatica
ISSN 2065-9601 · Babes-Bolyai University, Cluj-Napoca · 108 artikel di indeks
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Artikel Jurnal
Pydsbuilder – A Dataset Builder Written in Python Django
Data mining and the analysis of open-source projects have become crucial in recent research, driven by the vast availability of data across multiple programming domains. This paper focuses on two main objectives: first, to present an experience report for designing a software quality data mining…
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Electric Vehicle Routing Problem: A Review of Recent Approaches and Algorithms
With the rapid advancement of new energy vehicles, electric vehicles (EVs) have become integral to modern transportation systems. Compared with traditional fuel vehicles, EVs are limited by their limited battery capacity and require reasonable charging planning to complete the designated routes…
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OLDIES BUT GOLDIES: THE POTENTIAL OF CHARACTER N-GRAMS FOR ROMANIAN TEXTS
This study addresses the problem of authorship attribution for Romanian texts using the ROST corpus, a standard benchmark in the field. We systematically evaluate six machine learning techniques — Support Vector Machine (SVM), Logistic Regression (LR), k-Nearest Neighbors (k-NN), Decision Trees…
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NETWORK OPTIMIZATION PROBLEM APPLICABLE FOR BREAST CANCER SCREENING COST MINIMIZATION
We investigate the problem of breast cancer screening optimization, using various techniques applicable in domains where the data format is not defined in advance. The aim is to minimize the cost related to the screening of patients while maximizing the beneficial effect of the process regarding…
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THE G1 GAUSSIAN-TYPE RESOURCE ALLOCATION POLICY FOR VIRTUALIZED DATA CENTERS: THE SCALING PROBLEM AND VARIATION OF PARAMETERS
Virtualized data centers use techniques such as resource consolidation to reduce the energy consumption and load balancing methods to improve performance. A previously proposed resource allocation policy of Gaussian type, named G1, has a behaviour in-between resource consolidation and load…
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WORD AND PUNCTUATION N-GRAM FEATURES IN ROMANIAN AUTHORSHIP ATTRIBUTION
This study addresses the problem of authorship attribution for Romanian texts, focusing on the use of N-gram features with an emphasis on semantic-independent representations. While character N-grams have been previously studied, this work extends the exploration to word and part-of-speech (POS)…
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BERT-BASED AUTHORSHIP ATTRIBUTION ON THE ROMANIAN DATASET CALLED ROST
Having been around for decades, the problem of authorship attribution remains a current focus. Some of the more recent instruments used are the pre-trained language models, the most prevalent being BERT. Here we used such a model to detect the authorship of texts written in the Romanian language…
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MONEY LAUNDERING DETECTION USING GRAPH NEURAL NETWORKS ENHANCED WITH AUTOENCODER COMPONENTS
The paper addresses the topic of detecting money laundering operations in transaction data represented as graph data-structures. We propose the integration of autoencoder components in Graph Neural Networks (GNN) architectures, in order to incorporate a reconstruction step in the traditional edge…
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Langdes: A New Approach for Improving the Performance of Prompt-based Image Editing in Interior Design Setting
The topic of instruction-based image editing has gotten a lot of attention in recent years with a lot of research conducted due to its immense potential in various applications such as removing unwanted details present in existing images or improving them. However, one of the main problems in…
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Deep Learning Approaches for Detecting Text Generated by Artificial Intelligence
Large language models have been a hot topic for discussion and research for quite a few years, allowing them to infiltrate in many industries, especially education. Their rise in popularity among students was caused by their vast capabilities in giving quick and reliable answers to questions on any…
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HardML: A Benchmark for Evaluating Data Science and Machine Learning Knowledge and Reasoning in AI
We present HardML, a benchmark designed to evaluate the knowledge and reasoning abilities in the fields of data science and machine learning. HardML comprises a diverse set of 100 challenging multiple- choice questions, handcrafted over a period of 6 months, covering the most popular and modern…
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Matching Apictorial Puzzle Pieces Using Deep Learning
Finding matches between puzzle pieces is a difficult problem relevant to applications that involve restoring broken objects. The main difficulty comes from the similarity of the puzzle pieces and the very small difference between a pair of pieces that almost match and one that does. The proposed…
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A Comprehensive Evaluation of Rough Sets Clustering in Uncertainty Driven Contexts
This paper presents a comprehensive evaluation of the Agent BAsed Rough sets Clustering (ABARC) algorithm, an approach using rough sets theory for clustering in environments characterized by uncertainty. Several experiments utilizing standard datasets are performed in order to compare ABARC against…
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3D Deformable Object Matching Using Graph Neural Networks
Considering the current advancements in computer vision it can be observed that most of it is focused on two-dimensional imagery. This includes problems such as classification, regression, and the lesser-known object matching problem. While object matching ca be viewed as a solved problem in a…
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Automatic Detection of Verbal Deception in Romanian With Artificial Intelligence Methods
Automatic deception detection is an important task with several applications in both direct physical human communication, as well as in computer-mediated one. The objective of this paper is to study the nature of deceptive language. The primary goal of this study is to investigate deception in…
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Competitive Influence Maximization in Trust-Based Social Networks With Deep Q-Learning
Social network analysis is a rapidly evolving research area having several real-life application areas, e.g. digital marketing, epidemiology, spread of misinformation. Influence maximization aims to select a subset of nodes in such manner that the information propagated over the network is…
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MALICIOUS WEB LINKS DETECTION - A COMPARATIVE ANALYSIS OF MACHINE LEARNING ALGORITHMS
One of the most challenging categories of threats circulating in the online world is social engineering, with malicious web links, fake news, clickbait, and other tactics. Malware URLs are extremely dangerous because they represent the main propagating vector for web malware. Malicious web links…
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Software Maintainability and Refactorings Prediction Based on Technical Debt Issues
Software maintainability is a crucial factor impacting cost, time and resource allocation for software development. Code refactorings greatly enhance code quality, readability, understandability and extensibility. Hence, accurate prediction methods for both maintainability and refactorings are…
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COROUTINES COMUNICATIONS. DESIGN AND IMPLEMENTATION ISSUES IN C++20
This paper explores the communication mechanisms and patterns available to coroutines to cooperate with one another. It investigates the issues in designing and implementing a framework for using C++20 coroutines effectively, for generators, asynchronous function calls, and especially asynchronous…
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EXTENDED MAMMOGRAM CLASSIFICATION FROM TEXTURAL FEATURES
The efficient analysis of digital mammograms has an important role in the early detection of breast cancer and can lead to a higher percentage of recovery. This paper presents an extended computer-aided diagnosis system for the classification of mammograms into three classes (normal, benign and…