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A General Overview on the Current State of Computer-aided Translation
(Technical University of Cluj-Napoca, 2024-04-28) SZASZ Maria Augusta , OLT Maria-Cristina
Computer-aided translation software has been around for decades facilitating the production of accurate and consistent translations in all fields. The two major competitors in computer-assisted translation (Trados and MemoQ) have managed to ease the professionals’ work and help them produce more accurate translations. Machine translation as we know it today either if we use Google or DeepL Translate or even parallel corpora have made a quantum leap in the past years, being usable and useful in everyday context. This paper describes the types and categories of computer-aided translation technologies in use, their applicability, advantages and limitations. It will address the limitations openly and argue that the revision / post-editing process is key to producing quality translations. It will approach the features of the models based on the authors’ concrete examples. The examples contain excerpts from the translations made by the authors into/from English into/from Romanian and Hungarian.
A NUMERICAL MODEL FOR I/Q MODULATION/DEMODULATION FOR AN FPGA-ENABLED SDR PLATFORM
(Technical University of Cluj-Napoca, 2023-06-21) BOTA Bianca L.M. ; BUTA Rareș ; KIREI Botond S. ; FĂRCAȘ Calin A. ; HINTEA Sorin A.
This paper presents a numerical model for I/Q modulation/demodulation implemented in Matlab. This numerical model serves as a starting point for the HDL/FPGA implementation of a baseband processor for a previously developed SDR platform. The numerical model verification is carried out by performing 4, 8, 64, and 256-point QAM transmission over an additive White Gaussian Noise Channel and by comparing numerical and theoretical bit error rates. A partial HDL implementation of the baseband processor is given: the baseband processor generates a 1MHz tone signal that is mixed by the RF fronted, generating a double sideband modulated signal.
AI in Language Learning and Teaching through the Magnifying Glass
(Technical University of Cluj-Napoca, 2024-04-28) CODREANU Florina
The present scene of AI development is more than ever polarized by two fundamental sides: pessimistic and gloomy on the one hand, though hopeful and enthusiastic on the other hand. ELT practitioners and professionals tend to favour the latter attitude and bring the current situation to their own advantage. In the recent years AI in language teaching and learning has conquered a few areas that before seemed reserved to teachers only. The impact is considered huge and the benefits undeniable. AI progress through the magnifying glass shows the researcher many opportunities and innovations, but also plenty of risks and even more limitations. The fore article follows, both narratively and critically, the dazzling encounter between AI tools and the ample field of teaching and learning foreign languages, especially English language. The meeting is not novel at all, nor the worrisome questions arisen along. However, a closer approach may cast some fresh light on this contradictory, still evolving matter of AI technology behind the process of teaching and learning.
AN ANALYSIS OF THE PERFORMANCE OF DIFFERENT DPSK MODULATION DATA FORMATS USING CROSS-POLARIZATION MODULATION BASED 80 Gb/s ALL-OPTICAL WAVELENGTH CONVERSION IN A SINGLE WIDEBAND SOA
(Technical University of Cluj-Napoca, 2024-06-07) SAROJINI R; SIVANANTHA Raja; SELVENDRAN S
At key optical network nodes the efficient deployment of WDM/DWDM technologies can be made possible by wavelength conversion. In this research, Cross-Polarization Modulation (XpolM) based All-Optical Wavelength Conversion (AOWC) using wide band Semiconductor Optical Amplifier (SOA) is obtained. The effectiveness of various optical differential phase modulations on wavelength conversion is analysed. NRZ-DPSK/DPSK, 33%RZ-DPSK, 50%RZ-DPSK and 67%RZ-DPSK/CSRZ-DPSK are investigated here. The data rate is 80 Gb/s and the conversion bandwidth is 1.04 nm. The analysis is extended for Linear, Lorentzian and No-approximation material gain simulation models. The NRZ-DPSK performs better in terms of maximum coupled intensity and ellipticity. CSRZ-displays a power spectral gain of up to 12 dB and shows narrower spectral width.
AUDIO DENOISING USING U-NET ARCHITECTURE
(Technical University of Cluj-Napoca, 2025-06-27) JIMON, L.-Daniel; VAIDA Mircea-F.
Audio denoising is a pivotal task in audio signal processing. This paper presents a machine learning approach using a U-Net architecture to denoise musical audio signals affected by four distinct noise types: white noise, urban noise, reverberation, and noise cancellation artifacts. The model was evaluated on datasets derived from IRMAS and UrbanSound8K. Objective and subjective evaluation metrics were used, which show the model's effectiveness in filtering white and urban noise. However, performance on reverberation and noise cancellation artifacts is limited, indicating areas for future architectural and methodological improvements.
CHATBOT DESIGNED FOR INTERNATIONAL STUDENTS
(Technical University of Cluj-Napoca, 2024-05-20) BULZESCU Carla-Mihaela; GRAMA Lacrimioara
The main purpose of this paper is to present a chatbot developed for international students. It provides guidance on a range of challenges, including safety, culture shock, housing, language, and academic notes. For this purpose, a dataset of 72 question-and-answer intents was developed from scratch, designed to assist students. The training phase uses the dataset to create the neural network model. The chatbot makes use of established rules and techniques for natural language processing to predict the appropriate responses to user’s demand. Two Python-based versions of the chatbot are developed: one with a user interface, designed using a Flask server connected to a front-end section, and one with a compiler-based method that can handle speech input and output. Both versions achieved high accuracy during the training phase, suggesting good forecasting for the purpose upon which the chatbot was designed.
DDoS ATTACK DETECTION USING SUPERVISED MACHINE LEARNING ALGORITHMS OVER THE CIDDOS2019 DATASET
(Technical University of Cluj-Napoca, 2023-06-22) ZINCA Daniel; DOBROTA Virgil
Distributed Denial-of-Service (DDoS) attacks are one of the most common types of cyber-attacks that can cause severe damage to networks and systems. Traditional methods to detect them rely on signature-based Intrusion Detection Systems (IDS), which are limited by the need of prior knowledge of specific patterns and by the usual ineffectiveness against zero-day attacks. However machine learning (ML) algorithms have the potential to support the detection of new and unknown attacks. This article compares the DDoS detection performance of three Machine Learning techniques: Gaussian Naïve Bayes, Logistic Regression and Random Forest, based on validation metrics such as precision, recall and F1 score. The system was trained using three datasets extracted from CICDDoS2019 database. The results proved the detection of attacks at Layer 4 (TCP SYN/ UDP flood), and at reflective Layer 7 (MSSQL, NetBIOS). The Random Forests and Logistic Regression methods achieved a precision between 93.7% and 99.4 % over these three datasets.
DECISION TREES-BASED ALGORITHM FOR INTELLIGENT ALLOCATION OF PROCESSES IN CLOUD
(Technical University of Cluj Napoca, 2025-06-25) DOLCESCU Constantin-Valentin; BOTEZ Robert; ZINCA Daniel; DOBROTA Virgil
The paper presents a decision tree–based scheduler for intelligent cloud process allocation that evaluates features such as source area, instruction count, payload size, priority, throughput, and delay to guide real-time placement decisions. The model was trained and validated on a diverse, scenario-driven synthetic dataset covering four controlled workload conditions plus randomized fallback cases. For the training dataset, the classifier achieved 93% accuracy, while for the validation and test set, an accuracy of 92% was obtained. A Kubernetes-inspired simulation framework further visualizes and confirms the scheduler’s allocation logic under dynamic conditions. These results underscore the approach’s effectiveness, interpretability, and suitability for production-grade cloud orchestration.
DESIGN AND IMPLEMENTATION OF A FULL-DUPLEX GROUND STATION FOR THE QO-100 SATELLITE SYSTEM BASED ON SDR AND RASPBERRY PI
(Technical University of Cluj-Napoca, 2024) CRIȘAN Nicolae
Abstract: This paper proposes an approach based on the Adalm-Pluto SDR and Raspberry PI to design a ground station for geostationary satellite communications. The system is designed from modules to be versatile, agile, and scalable. In this case, the usage of modules is mandatory due to the complexity of the communications system, which simultaneously operates two radio channels at 2.4 GHz for uplink and 10 GHz for downlink. Such a combination with SDR (Software Defined Radio) and classic down and up converters benefits from using a Raspberry PI 4 with a powerful processor running under Linux. The proposed system allows the usage of GNU Radio with its powerful graphical interface written in Python. User interface UI has been undertaken by the Raspberry PI’s most versatile display with a touch screen of 7 inches. Another topic the paper addresses is using the helical antenna in front of the Horn antenna at the same focus point established by the dish reflector. The ground station proposed here has been successfully tested to transmit short radio packages containing data about temperature, atmospheric conditions, and voice.
INTEGRATION OF THE SURICATA INTRUSION DETECTION SYSTEM AND OF THE WAZUH SECURITY INFORMATION AND EVENT MANAGEMENT FOR REAL-TIME DENIAL-OF-SERVICE AND DATA TAMPERING DETECTION AND ALERTING
(Technical University of Cluj-Napoca, 2024) ANDREICA Gheorghe-Romeo ; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
This paper addresses one of the cybersecurity challenges posed by the rapid growth of IoT and intelligent transport systems. It aims to develop a security monitoring and alerting system for GPS devices in these systems, integrating the Suricata Intrusion Detection System (IDS) mechanism and the Wazuh Security Information and Event Management (SIEM). The solution is focused on detecting, alerting and real-time monitoring for Denial-of-Service (DoS) and Data Tampering attacks, ensuring robust protection against emerging cyber threats in IoT GPS tracking systems
INTRODUCTION TO CYCLIC CODES AND ILLUSTRATION OF THEIR IMPLEMENTATION THROUGH LINEAR FEEDBACK SHIFT REGISTERS WITHIN A PROGRESSIVE WEB APPLICATION
(Technical University of Cluj-Napoca, 2024-06-02) SOFIA Ioana Lavinia
This paper provides an introductory overview of cyclic codes of Hamming type and showcases their effectiveness in detecting and correcting errors in digital communications. Thus, a Progressive Web Application has been developed through React.js and p5.js JavaScript libraries to simulate the coding operations using Linear Feedback Shift Registers. This GUI serves an educational purpose, being used in Information Transmission Theory laboratories so that students could easier comprehend this particular coding scheme. The results obtained highlight the efficiency of developed software application in the e-learning process of cyclic code of Hamming type and its adeptness in error detection and correction within digital communications.
KUBERNETES CONFIGURATION FILES CREATED WITH A PYTHON QUART WEB INTERFACE FOR REAL LIFE SCENARIOS OF KUBERNETES DEPLOYMENTS
(Technical University of Cluj-Napoca, 2024-11-29) DUMITRE Ioan-Alexandru; RUGINA Szabolcs-Gavril; LENGYEL Laszlo-Csongor; RUS Andrei-Bogdan; DOBROTA Virgil
This paper presents the development of a web interface using Python Quart to simplify the creation and management of Kubernetes manifest files. The interface allows users to create, update, delete, and manage Kubernetes resources through an intuitive platform. Developed using Test-Driven Development (TDD) principles, the application minimizes errors and improves reliability by ensuring that each component is rigorously tested before deployment. By leveraging Quart’s asynchronous capabilities, it handles multiple requests efficiently, enhancing scalability and performance. Performance tests with Locust and real-time monitoring with Prometheus show the system's ability to manage multiple users and highlight areas for improvement in request latency.
MOBILE APPLICATION FOR BLE INDOOR POSITIONING
(Technical University of Cluj-Napoca, 2023-12-12) MĂLUȚAN Raul; BRISC Bianca
Distance estimation in indoor localization is mainly solved by Received Signal Strength Indicator (RSSI). In our approach, the RSSI is determined empirically, and it’s used to estimate the distance between the user and beacons in a mobile app solution. Trilateration and Kalman filter help obtain better accuracy. The paper proposes a classical solution for indoor localization, but with features like blueprint implementation, Google Maps integration, and manual beacon positioning.
Remarks on the Legitimation Discourse of Text Generation. An Analysis of Writing Teaching Programs
(Technical University of Cluj-Napoca, 2024-04-28) POLICSEK Cecilia
The current article compares a number of underlying principles that have legitimized the benefit of reading and writing within the educational framework throughout the course of time with the recent discourse on Artificial Intelligence (AI) text generation. It does so by revising several ideas that have traditionally supported the study of reading and writing and contrasts them with the perceived benefits and threats of AI, as formulated by a number of important university writing programs. This contrastive consideration of the support of reading and writing, on the one hand, and the discourse on text generation, on the other, is meant to contribute to the assessment of the degree to which the notion of text generation-centered education is compatible with education, as defined by Humanistic standards.
Revising Research Papers in English to Avoid Desk Rejection
(Technical University of Cluj-Napoca, 2024-04-28) MUREȘAN Carmen
In the rapidly expanding landscape of academic publishing, adhering to English for Research Publication Purposes (ERPP) standards presents significant challenges for second language (L2) writers. Beyond linguistic proficiency, mastering academic discourse conventions and argumentation structures is essential. Romanian researchers, in particular, face obstacles due to linguistic and structural differences between Romanian and English. These include mastering academic style, accurately translating technical terminology, and adapting to the conventions of international scholarly writing. Limited access to high-quality language support services and the pressure to publish in high-impact journals further complicate the process. These challenges not only hinder the clarity and coherence of research papers but also increase the risk of desk rejection, preventing valuable contributions from reaching the global academic community. By analyzing the revision of approximately 200 pages of Medical Robotics research intended for international journals, this study highlights the specific obstacles encountered in manuscript preparation and the role of revision in mitigating the risk of desk rejection. Furthermore, it underscores the need for structured training programs and language support mechanisms tailored specifically for non-native researchers to improve their writing skills and overall publishing success.
SECURE ACCESS WITH TELTONIKA GPS TRACKING DEVICES FOR INTELLIGENT TRANSPORTATION SYSTEMS
(Technical University of Cluj-Napoca, 2023-03-27) ANDREICA Gheorghe-Romeo; STANGU Ciprian; IVANCIU Iustin-Alexandru; ZINCA Daniel; DOBROTA Virgil
GPS tracking devices are widely used in industries like logistics, transportation, and security. However, they are susceptible to cyber-attacks, including Man-in-the-Middle (MITM). This study focuses on Teltonika GPS tracking devices and examines the impact of MITM attacks on their operation. We propose implementing encryption protocols and other measures to enhance the security and resilience of Teltonika GPS tracking devices.
SECURITY ISSUES IN INTERNET OF THINGS BOTNETS: A HIGH INTERACTION HONEYPOT APPROACH
(Technical University of Cluj-Napoca, 2023-12-11) LAZAR Alexandru; BLAGA Tudor-Mihai; ZINCA Daniel; DOBROTA Virgil
For a better awareness of the tactics employed by the malicious entities in Internet of Things, a system called Honeypot tricks the attackers into exploiting its “sweet” fake resources. While implementing nine types of devices only six of those were attacked. Despite this, the honeypot managed to capture attacks destined for three devices that were not implemented. Overall, several real-world attacks were captured and analyzed providing different indicators of compromise. No new threats were identified but the server only ran for a short period of time and with limited resources. This approach looks like a promising avenue for creating attacker profiles and collecting data on botnet behavior.
SPATIAL-SPECTRAL CLASSIFICATION OF HYPERSPECTRAL DATA WITH CONTROLLED DATA SEPARATION
(Technical University of Cluj-Napoca, 2023-06-22) MICLEA Andreia Valentina; ABRUDAN Mihaela
Exploring spatial-spectral data frequently involves classifying hyperspectral images using convolutional neural networks. Due to the high complexity of the data and the scarcity of available training samples, hyperspectral image classification presents significant difficulties. In the context of supervised classification, we find that traditional experimental designs are frequently misused in the spectral-spatial processing context, resulting in unfair or biased performance evaluation, particularly when training and testing samples are selected at random from the same dataset. Under these circumstances, the dependence caused by the overlap between training and testing samples may be artificially increased, in breach of the data independence assumption upheld by supervised learning theory. In order to prevent an unbiased classification result, we present in this paper a controlled strategy designed to minimize the overlap between the samples present in the training and the testing data sets. The proposed controlled sampling strategy ensures a more trustworthy generalization of the CNN model by minimizing the issues present in the random sampling approach, such as the inability to determine whether or not an increase in classification accuracy is due to the spatial information incorporated into a classifier or to an increase in the overlap between training and testing data sets. Experiments performed with a wavelet CNN on different HSIs, namely Indian Pines, Pavia University, and Salinas, ensure the generalization of the data under the assumption that the training and data sets are independent from one another, based on a controlled strategy. Considering the high dimension of the HSI image, as a pre-processing step, the evaluation of the proposed framework is done by PCA and FA methods.
TEXTURE BASED POLARIMETRIC SYNTHETIC APERTURE RADAR IMAGE CLASSIFICATION USING COVARIANCE MATRICES
(Technical University of Cluj-Napoca, 2025-06-26) ILEA Ioana; MICLEA-CECALACA Andreia Valentina; CISLARIU Mihaela; MALUTAN Raul; GROSU George
This paper proposes a workflow for polarimetric SAR (PolSAR) image classification based on statistical texture descriptors. The methodology presented in this paper involves spatial interdependence between neighboring pixels as well as multiscale texture representation using wavelet decomposition. The collected features are modeled by zero-mean Multivariate Gaussian Distributions (MGDs). Then, their estimated covariance matrix acts as the texture descriptor and is employed in a k-nearest neighbors (kNN) classifier. Experiments using real PolSAR data validate the proposed approaches' accuracy in land cover categorization, showing their potential for reliable class identification.
The Importance of Reflection in Language Teaching
(Technical University of Cluj-Napoca, 2024-04-28) RUSU Delia-Georgeta , LITERAT Ruxanda
Reflective practice plays an important role in the professional development of language instructors, allowing them to critically assess their teaching approaches, rethink instructional strategies, and respond effectively to student needs. This article delves into the concept of reflective practice in language teaching, by examining the theoretical foundations of reflection in education, key reflective models such as Kolb's Experiential Learning Cycle and Schön's theories, and discussing strategies for language educators to maximize the benefits of reflection. It also explores the emotional aspects of reflection, emphasizing their role in teacher development and resilience. By integrating reflective practice into language teaching, educators can create more dynamic and effective learning environments while advancing their professional expertise.