bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhancing Adversarial Examples for Evading Malware Detection Systems: A Memetic Algorithm Approach
Authors:   University Constantine 2, Abdelhamid Mehri, Faculty of New Technologies of Information and Communication, Department of Computer Science, 25000, Algéria, Ghanem Khadoudja , Kherbache Ziad , Ourdighi Omar
Published: February 2025

Malware detection using Machine Learning techniques has gained popularity due to their high accuracy. However, ML models are susceptible to Adversarial Examples, specifically crafted samples intended to deceive the detectors. This paper presents a novel method for generating evasive AEs by augmenting existing malware with a new section at the end of the PE file, populated with binary data using memetic algorithms. Our method hybridizes global search and local search techniques to achieve optimized results. The Malconv Model, a well-known state-of-the-art deep learning model designed explicitly for detecting malicious PE files, was used to assess the evasion rates. Out of 100 tested samples, 98 successfully evaded the MalConv model. Additionally, we investigated the simultaneous evasion of multiple detectors, observing evasion rates of 35% and 44% against KNN and Decision Tree machine learning detectors, respectively. Furthermore, evasion rates of 26% and 10% were achieved against Kaspersky and ESET commercial detectors. In order to prove the efficiency of our memetic algorithm in generating evasive adversarial examples, we compared it to the most used evolutionary-based attack: the genetic algorithm. Our method demonstrated significantly superior performance while utilizing fewer generations and a smaller population size.
Enhancing Web Security through Machine Learning-based Detection of Phishing Websites
Authors:   Palestine Technical University Kadoorie / Computer Science Department, Faculty of Information Technology, Tulkarm, P.O Box 305, Palestine, Odeh Najla , Eleyan Derar , Eleyan Amna
Published: February 2025

The rise of cyberattacks has led to an increase in the creation of fake websites by attackers, who use these sites for advertising products, transmit malware, or steal valuable login credentials. Phishing, the act of soliciting sensitive information from users by masquerading as a trustworthy entity, is a common technique used by attackers to achieve their goals. Spoofed websites and email spoofing are often used in phishing attacks, with spoofed emails redirecting users to phishing websites in order to trick them into revealing their personal information. Traditional solutions for detecting phishing websites rely on signature-based approaches that are not effective in detecting newly created spoofed websites. To address this challenge, researchers have been exploring machine-learning methods for detecting phishing websites. In this paper, we suggest a new approach that combines the use of blacklists and machine learning techniques such that a variety of powerful features, including domain-based features, abnormal features, and abnormal features based on URLs, HTML, and JavaScript, to rank web pages and improve classification accuracy. Our experimental results show that using the proposed approach, the random forest classifier offers the best accuracy of 93%, with FPR and FNR as 0.12 and 0.02, with a Precision of 90%, Recall of 97% an F1 Score of 93%, and MCC of 0.85.
Modified CNN Model for Network Intrusion Detection and Classification System Using Local Outlier Factor-based Recursive Feature Elimination
Authors:   Department of Computer Science Engineering, Adikavi Nannaya University, Rajamahendravaram Andhra Pradesh, 533296, India, Mounika Kondru , Rao P. Venkateswara , Anbalagan Anand
Published: February 2025

An intrusion detection system (IDS) is either a part of a software or hardware environment that monitors data and analyses it to identify any attacks made against a system or a network. Traditional IDS approaches make the system more complicated and less efficient, because the analytical properties process is difficult and time-consuming. This is because the procedure is complex. Therefore, this research work focuses on a network intrusion detection and classification (NIDCS) system using a modified convolutional neural network (MCNN) with recursive feature elimination (RFE). Initially, the dataset is balanced with the help of the local outlier factor (LOF), which finds anomalies and outliers by comparing the amount of deviation that a single data point has with the amount of deviation that its neighbors have. Then, a feature extraction selection approach named RFE is applied to eliminate the weakest features until the desired number of features is achieved. Finally, the optimal features are trained with the MCNN classifier, which classifies intrusions like probe, denial-of-service (DoS), remote-to-user (R2U), user-to-root (U2R), and identifies normal data. The proposed NIDCS system resulted in higher performance with 99.3% accuracy and a 3.02 false alarm rate (FAR) as equated to state-of-the-art NIDCS approaches such as deep neural networks (DNN), ResNet, and gravitational search algorithms (GSA).
Recognizing Fakes, Propaganda and Disinformation in Ukrainian Content based on NLP and Machine-learning Technology
Authors:   Information Systems and Networks Department, Lviv Polytechnic National University, Lviv, 79013, Ukraine, Vysotska Victoria , Przystupa Krzysztof , Kulikov Yurii , Chyrun Sofiia , Ushenko Yuriy , Hu Zhengbing , Uhryn Dmytro
Published: February 2025

The project envisages the creation of a complex system that integrates advanced technologies of machine learning and natural language processing for media content analysis. The main goal is to provide means for quick and accurate verification of information, reduce the impact of disinformation campaigns and increase media literacy of the population. Research tasks included the development of algorithms for the analysis of textual information, the creation of a database of fakes, and the development of an interface for convenient access to analytical tools. The object of the study was the process of spreading information in the media space, and the subject was methods and means for identifying disinformation. The scientific novelty of the project consists of the development of algorithms adapted to the peculiarities of the Ukrainian language, which allows for more effective work with local content and ensures higher accuracy in identifying fake news. Also, the significance of the project is enhanced by its practical value, as the developed tools can be used by government structures, media organizations, educational institutions and the public to increase the level of information security. Thus, the development of this project is of great importance for increasing Ukraine's resilience to information threats and forming an open, transparent information society.
Metaheuristic-enhanced Deep Learning Model for Accurate Alzheimer's Disease Diagnosis from MRI Imaging
Authors:   Department of Electronics & Communication Engineering, Kalasalingam Academy of Research and Education, TamilNadu, India, A.V. Nisha , Rajasekaran M. Pallikonda , Kottaimalai R. , Vishnuvarthanan G. , Arunprasath T. , Muneeswaran V. , Priya R. Krishna
Published: February 2025

Alzheimer’s Disease (AD) is the neuro-degenerative dementia, where the precise and early recognition of AD is vital for timely treatment to reduce mortality rate. A new automated model is implemented in this work for early discovery of AD in the Magnetic Resonance Imaging (MRI) brain scans. Initially, the input brain scans are taken from the Alzheimer's disease Neuroimaging Initiative (ADNI) database. Further, the acquired raw brain scans are visually improved by employing the binary normalization technique. The denoised brain scans are fed to the pre-trained Convolutional Neural Network (CNN) named GoogleNet for feature extraction. Next, the extracted richer feature values are fed to the Long Short Term Memory (LSTM) network for classifying the brain scan as Normal Control (NC), Mild Cognitive Impairment (MCI) and AD. In this manuscript, a Honey Badger Optimization Algorithm (HBOA) technique is incorporated with the LSTM networks for hyper-parameters optimization, where this procedure helps in diminishing the LSTM network’s complexity and computational time. The experimental results conducted on the ADNI database underscore the HBOA-based LSTM network's effectiveness, showcasing a remarkable mean classification accuracy of 97.83% in multi-class classification. Moreover, the sensitivity of HBOA based LSTM for AD/NC is 96.73% which is high when compared to the existing methodologies such as SVM with radial basis kernel function and NCSINs. This performance surpasses that of other comparative models for AD detection, emphasizing the superior capabilities and potential of the proposed method in the early detection.
Machine Learning based Wildfire Area Estimation Leveraging Weather Forecast Data
Authors:   Department of Computer Engineering, Mukesh Patel School of Technology Management & Engineering, SVKM's Narsee Monjee Institute of Management Studies (NMIMS) Deemed-to-University Mumbai, Maharashtra, India, Sultania Saket , Sonawane Rohit , Kanikar Prashasti
Published: February 2025

Wildfires are increasingly destructive natural disasters, annually consuming millions of acres of forests and vegetation globally. The complex interactions among fuels, topography, and meteorological factors, including temperature, precipitation, humidity, and wind, govern wildfire ignition and spread. This research presents a framework that integrates satellite remote sensing and numerical weather prediction model data to refine estimations of final wildfire sizes. A key strength of our approach is the use of comprehensive geospatial datasets from the IBM PAIRS platform, which provides a robust foundation for our predictions. We implement machine learning techniques through the AutoGluon automated machine learning toolkit to determine the optimal model for burned area prediction. AutoGluon automates the process of feature engineering, model selection, and hyperparameter tuning, evaluating a diverse range of algorithms, including neural networks, gradient boosting, and ensemble methods, to identify the most effective predictor for wildfire area estimation. The system features an intuitive interface developed in Gradio, which allows the incorporation of key input parameters, such as vegetation indices and weather variables, to customize wildfire projections. Interactive Plotly visualizations categorize the predicted fire severity levels across regions. This study demonstrates the value of synergizing Earth observations from spaceborne instruments and forecast data from numerical models to strengthen real-time wildfire monitoring and postfire impact assessment capabilities for improved disaster management. We optimize an ensemble model by comparing various algorithms to minimize the root mean squared error between the predicted and actual burned areas, achieving improved predictive performance over any individual model. The final metric reveals that our optimized WeightedEnsemble model achieved a root mean squared error (RMSE) of 1.564 km2 on the test data, indicating an average deviation of approximately 1.2 km2 in the predictions.
Fuzzy Hybrid Meta-optimized Learning-based Medical Image Segmentation System for Enhanced Diagnosis
Authors:   Department of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India, J. Nithisha , Visumathi J. , Rajalakshmi R. , Suseela D. , Sudha V. , Choubey Abhishek , Farhaoui Yousef
Published: February 2025

This medical image segmentation plays a fundamental role in the diagnosis of diseases related to the correct identification of internal structures and pathological regions in different imaging modalities. The conventional fuzzy-based segmentation approaches, though quite useful, still have some drawbacks regarding handling uncertainty, parameter optimization, and high accuracy of segmentation with diverse datasets. Because of these facts, it generally leads to poor segmentations, which can give less reliability to the clinical decisions. In addition, the paper is going to propose a model, FTra-UNet, with advanced segmentation of medical images by incorporating fuzzy logic and transformer-based deep learning. The model would take complete leverage of the strengths of FIS concerning the handling of uncertainties in segmentation. Besides, it integrates SSHOp optimization technique to fine-tune the weights learned by the model to ensure improvement in adaptability and precision. These integrated techniques ensure faster convergence rates and higher accuracy of segmentation compared to state-of-the-art traditional methods. The proposed FTra-UNet is tested on BRATS, CT lung, and dermoscopy image datasets and ensures exceptional results in segmentation accuracy, precision, and robustness. Experimental results confirm that FTra-UNet yields consistent, reliable segmentation outcomes from a practical clinical application perspective. The architecture and implementation of the model, with the uncertainty handled by FIS and the learning parameters optimization handled by the SSHOp method, increase the power of this model in segmenting medical images.
NIPP: Non-Invasive PCOS Prediction using XG-boost Machine Learning Model
Authors:   Chitkara University Institute of Engineering & Technology, Chitkara University, Punjab, India, Prasher Shikha , Nelson Leema , Gafar Manal
Published: February 2025

Polycystic Ovary Syndrome (PCOS) is a common endocrine disorder that affects women of reproductive age, leading to hormonal imbalances and ovarian dysfunction. Early detection and intervention are vital for effective management and prevention of complications. This study compares PCOS prediction using the XGBoost machine learning model against four traditional models: Logistic Regression (LR), Support Vector Machine (SVM), Decision Trees (DT), and Random Forests (RF). LR and SVM achieve accuracies of 95% and 96%, respectively, demonstrating strong predictive capabilities. In contrast, DT had a lower accuracy (82%), indicating limitations in PCOS data complexity. RF showed competitive performance with 96% accuracy, underscoring its effectiveness in ensemble learning. XGBoost achieves 98% accuracy with its parameter configuration. The scale pos weight parameter adjusts the positive class weight in im- balanced datasets, addressing underrepresentation by assigning more weight to the minority class, and thereby improving the training focus. The gradient boosting framework incrementally builds models to address complex feature interactions and dependencies, enhancing the accuracy and stability in predicting intricate PCOS dataset. This analysis highlights the importance of advanced machine learning models such as XGBoost for accurate and reliable PCOS predictions. This re- search advances PCOS prediction, demonstrates the potential of machine learning in healthcare, and clarifies the strengths and limitations of different algorithms with complex medical datasets.
An Accented Character-based Captcha System with Usability Test Using Solving Time and Response Time
Authors:   Federal College of Animal Health and Production Technology, Department of Computer Science, Apata Ibadan, Nigeria, O. T. Olanrewaju , A. A. Omilabu , C. V. Nwufoh , F. O. Adewale , O. Osunade
Published: February 2025

CAPTCHA is an acronym for Completely Automated Public Turing test to tell Human and Computer Apart. The main purpose of CAPTCHA is to differentiate between human and automated machine during online transaction. Text, image, audio and video are types of CAPTCHAs. However, text-based CAPTCHAs are available in the market in different languages i.e., English, Arabic, Urdu and Chinese but accented character-based text CAPTCHA system namely NAIJACAPTCHA is a newly introduce text-based CAPTCHA developed using Latin characters and accented characters from two Nigerian language: Yorùbá and Igbo. The usability of sixteen accented character-based CAPTCHAs was tested to see if they were suitable for human usage. The usability performance was measured using response time, solving time, accuracy, and success rate. A total of two hundred and twenty-two participants were selected for the study, and 1108 CAPTCHA codes were generated. The response time for Text Distortion with Coloured Background was the fastest, with 1.18×103 ms, while Coloured Texts with No Background (CTNB) had the least response time of 1.09 ms. With a solving time of 2.52×104 ms, Character Fragmentation with No Background was the fastest. The result showed that CTBN's response and problem-solving time is highly promising; as a result, its website application for authentication during online transactions to distinguish between humans and machines will be simple for human beings to solve and user requests will also be swiftly attended to. Lastly, the security aspect of the developed NAIJACAPTCHA will be looked into determine its vulnerability.
Становление и развитие органов прокуратуры на Северном Кавказе
Authors: Макаев А.А. , Маремкулов А.Н.
Published: February 2025

в статье рассмотрены вопросы становления и развития прокуратуры Северного Кавказа различные исторические периоды, проанализированы особенности изменения функций прокуратуры в зависимости от изменения формы правления, а также показана функции управления Генеральной прокуратуры Российской Федерации в Северного Кавказа. Уделено внимание, что прокурорско-судебная система на Северном Кавказе в своем становлении и развитии имела свои особенности, связанные с чередой событий, местными обычаями и культурой национальных образований.

the article examines the issues of the formation and development of the Prosecutor's Office of the North Caucasus in various historical periods, analyzes the peculiarities of changing the functions of the prosecutor's office depending on the change in the form of government, and also shows the functions of the office of the Prosecutor General of the Russian Federation in the North Caucasus. Attention is paid to the fact that the prosecutorial and judicial system in the North Caucasus in its formation and development had its own characteristics associated with a series of events, local customs and culture of national entities.
Проблемы преступности мигрантов в современной России
Authors: Горемыкин Д.Ю.
Published: February 2025

данная статья посвящена анализу преступности среди мигрантов в Российской Федерации. В работе рассматриваются статистические данные о преступлениях, совершаемых мигрантами в период за январь-сентябрь 2020 года по аналогичный период 2024 года. В работе рассматриваются примеры преступных действий, совершенных мигрантами на территории России. Анализируются причины, способствующие преступной деятельности среди мигрантов, включая трудности адаптации, языковой барьер, дискриминацию, нелегальное положение и участие в организованной преступности. В заключении предлагаются рекомендации по снижению уровня преступности среди мигрантов, основанные на улучшении миграционного законодательства, содействии интеграции и комплексном решении социальных и экономических проблем. Борьба с преступностью является важным аспектом в обеспечении национальной безопасности, поэтому важно принимать меры в борьбе с отдельными преступными интеграциями, динамика которых имеет ежегодный рост.

this article is devoted to the analysis of crime among migrants in the Russian Federation. The paper examines statistical data on crimes committed by migrants in the period from January-September 2020 to the same period in 2024. The paper examines examples of criminal acts committed by migrants on the territory of Russia. The reasons contributing to criminal activity among migrants are analyzed, including difficulties of adaptation, language barrier, discrimination, illegal situation and participation in organized crime. In conclusion, recommendations are proposed to reduce the crime rate among migrants based on improving migration legislation, promoting integration and comprehensively solving social and economic problems. The fight against crime is an important aspect in ensuring national security, therefore it is important to take measures to combat individual criminal integrations, the dynamics of which has an annual increase.
Специальная военная операция и режим военного положения: вопросы административной ответственности субъектов
Authors: Макарова Ю.А.
Published: February 2025

в статье исследованы вопросы административной ответственности субъектов (физических, юридических и должностных лиц) при проведении специальной военной операции и режима военного положения за невыполнение обязательных решений высшего должностного лица субъекта Российской Федерации (Оперативного штаба или Штаба обороны). Представлен результат анализа норм, предусматривающих административную ответственность за невыполнение обязательных решений высшего должностного лица субъекта Российской Федерации (Оперативного штаба) с точки зрения федерального и регионального регулирования. Автор приходит к выводу, что ответственность за невыполнение решения высшего должностного лица субъекта Российской Федерации (Оперативного штаба), принятого в рамках его компетенции в соответствии с Указом Президента РФ от 19 октября 2022 г. № 757, установлена частично как на федеральном, так и на региональном уровне в ряде субъектов страны. При квалификации противоправных деяний следует учитывать, что ст. 20.36 КоАП РФ относится только к нарушениям требований в сфере территориальной обороны и не охватывает все субъекты и ситуации, которые урегулированы в рамках Указа Президента РФ от 19 октября 2022 г. № 757, а именно не может быть вменена физическим лицам и на территориях регионов России, где введен базовый режим готовности.

the article examines the issues of administrative liability of subjects (individuals, legal entities and officials) during a special military operation and martial law for failure to comply with mandatory decisions of the highest official of a constituent entity of the Russian Federation (Operational Headquarters or Defense Headquarters). The article presents the result of the analysis of the norms providing for administrative liability for failure to comply with mandatory decisions of the highest official of a constituent entity of the Russian Federation (Operational Headquarters) from the point of view of federal and regional regulation. The author concludes that liability for failure to comply with a decision of the highest official of a constituent entity of the Russian Federation (Operational Headquarters), adopted within the framework of his competence in accordance with the Decree of the President of the Russian Federation of October 19, 2022 No. 757, is partially established both at the federal and regional levels in a number of constituent entities of the country. When qualifying illegal acts, it should be taken into account that Art. 20.36 of the Code of Administrative Offenses of the Russian Federation applies only to violations of requirements in the field of territorial defense and does not cover all subjects and situations that are regulated within the framework of the Decree of the President of the Russian Federation of October 19, 2022 No. 757, namely, it cannot be imputed to individuals and in the territories of regions of Russia where a basic readiness regime has been introduced.
Транспортная безопасность: состояние и перспективы развития
Authors: Пичкур А.П.
Published: February 2025

за последние несколько лет ввиду появления новых угроз вопросы обеспечения транспортной безопасности в Российской Федерации стали особенно актуальными, что предопределило появление новых тенденций и направлений развития в данной области. Вместе с тем, не все закрепленные законодательно задачи в области транспортной безопасности имеют эффективные решения, что предопределяет необходимость проведения соответствующих исследований в данной сфере общественных отношений и выработку эффективных механизмов ее обеспечения, в частности, организационных, политических, нормативно-правовых и экономических. В статье автором делается вывод о том, что в настоящее время система субъектов, которые осуществляют управление в сфере обеспечения транспортной безопасности, нуждается в реформировании. Таким образом, наиболее очевидным видится такое направление государственной политики в области транспортной безопасности, которое было бы направлено на постоянное повышение ее уровня за счет развития и модернизации законодательных правил и норм путем их адаптации к существующим реалиям функционирования транспортной инфраструктуры и с учетом тех угроз транспортной безопасности, которые возникают в конкретный период времени. Иными словами, требования в области транспортной безопасности всегда должны соответствовать текущей ситуации, а последствия их несоблюдения субъектами транспортной безопасности должны быть достаточно жесткими для того, чтобы минимизировать случаи халатности.

over the past few years, due to the emergence of new threats to transport security, the issues of ensuring transport security in the Russian Federation have become particularly relevant, which predetermined the emergence of new trends in the field of transport security. At the same time, not all legally defined tasks in the field of transport security have an effective solution, which determines the need to conduct appropriate research in the field of transport security and develop appropriate effective mechanisms to ensure it, in particular, organizational, political, regulatory and economic.The system of entities that manage transport security needs to be reformed. Hence, the most obvious direction of the state policy in the field of transport security is focused on constantly improving the level of safety through the development and modernization of legislative rules and regulations by adapting them to the existing realities of the functioning of transport infrastructure and taking into account those threats to transport security that arise in a particular period. In other words, requirements in the field of transport security should always correspond to the current situation, and the consequences of non-compliance by transport security entities should be serious enough to minimize cases of negligence by such entities in the field of transport security.
Правовые основы молодежной политики в России
Authors: Ледянкина И.Ю.
Published: February 2025

данная статья посвящена анализу правовых основ молодежной политики в России. Важность молодежной политики обусловлена стремлением государства создать условия для полноценной реализации молодежи, ее социальной защищенности, занятости и активного участия в общественной жизни. Исследуются ключевые законодательные акты, регулирующие молодежную политику. Анализируются современные вызовы и тенденции, влияющие на молодежную политику в стране, и подчеркивается необходимость интеграции усилий государственных и частных структур для достижения эффективных результатов. В заключении обозначены перспективы дальнейшего развития молодежной политики в России.

this article is dedicated to the analysis of the legal foundations of youth policy in Russia. The importance of youth policy is determined by the state's desire to create conditions for the full realization of youth, its social protection, employment, and active participation in public life. Key legislative acts regulating youth policy are examined. Modern challenges and trends affecting youth policy in the country are analyzed, highlighting the necessity of integrating the efforts of public and private structures to achieve effective results. In conclusion, prospects for further development of youth policy in Russia are outlined.
Wisata Luhak Nan Tigo dalam Fotografi Nature
Authors: Fernando Nesta , Kurniadi Benny , Rahmat Aziz Fauzi
Published: February 2025

West Sumatra is one of the provinces in the Indonesian region which is famous for its natural beauty, especially natural tourism in Minangkabau which consists of Luhak Nan Tigo, namely Tanah Datar, Luhak Agam, and Luhak Limo Puluah Koto. Luhak Nan Tigo has a natural environment that is still pristine, has many beautiful and interesting tourist attractions through a photographic perspective that will be packaged through nature photography. Through the creation of nature photography works, the artist will display tourist attractions in Luhak Nan Tigo with several categories such as landscape, seascape, skyscape, and cityscape. The artist also uses several angles, namely, low angle, eye level, high angle or aerial. The resulting works amount to 20 photo works. The artist carried out several data collection methods such as literature studies, observations, and interviews, designing the work process, the embodiment of tools and materials in realizing the idea of creation. Through this nature photography, the artist can capture the natural beauty in Luhak Nan Tigo, by capturing the shape and characteristics of the tourist attraction. On the other hand, the creator also wants to make this work as an innovation in nature photography in Luhak Nan Tigo, and it can also be an archive of a tourist attraction in Luhak Nan Tigo over time if it is not managed properly anymore.
IMPLEMENTASI FORMULA HAVERSINE PADA SISTEM ABSENSI PEGAWAI BERBASIS WEB (STUDI KASUS: SMA ISLAM GUPPI KOTA SORONG)
Authors: Mursid Mursid , Hazani La Ode
Published: February 2025

SMA Islam GUPPI Kota Sorong yang berlokasi di Malabutor, Kecamatan Sorong Manoi, Kota Sorong, Papua Barat Daya. Dalam melakukan proses absensi masih berrsifat konvensional. Pegawai melakukan absensi masih harus diisi dengan cara ditulis pada daftar yang telah disediakan oleh staf tata usaha, yang bisa saja jam absensi dapat diubah ketika terlambat absensi. Pegawai yang bertugas di laboratorium komputer maupun perpustakaan kadang absensinya diisi ketika pulang, karena jarak tempat absensi yang cukup jauh. Hasil rekapan dan laporan absensi pegawai ke kepala sekolah masih manual yaitu masih berupa lembaran kertas. Menghasilkan sistem informasi absensi pegawai berbasis web dengan menerapkan formula haversine. Formula haversine digunakan untuk menghitung jarak diantara titik-titik yang ada pada permukaan bumi berdasarkan koordinat latitude dan longitude. Sistem yang dibuat berbasis web dengan menggunakan bahasa pemrograman PHP, Framework CodeIgniter4, MySQL, LeafletJS untuk peta dan tools pendukung seperti Visual Studio Code, WampServer, Balsamiq dan Visio. Hasil yang diperoleh dari penelitian adalah sistem informasi yang dapat mendeteksi lokasi pegawai dan absensi hanya dapat dilakukan dalam radius yang telah ditentukan, apabila diluar radius tidak dapat melakukan absensi.
SISTEM INFORMASI ABSENSI MENGGUNAKAN QR CODE PADA FAKULTAS ILMU KOMPUTER DAN MANAJEMEN USTJ BERBASIS WEB
Authors: Achmad Rizkial , Rety Aprianto
Published: February 2025

Absensi kehadiran merupakan bagian peranan penting dalam sector pendidikan. Dimana absensi merupakan salah satu penunjang utama yang dapat membantu pecatatan kehadiran dan memotivasi setiap kegiatan yang dilakukan. Seperti halnya absensi pada kampus Universitas Sains dan Teknologi Jayapura khususnya Fakultas Ilmu Komputer dan Manajemen yang melakukan tanda tangan dikertas ataupun menggunakan sistem siakad yang sudah ada. Akan tetapi, dalam proses absensi tersebut dosen melakukan pencatatan absensi secara manual pada media kertas, dosen harus masuk ke dalam website siakad untuk melakukan absensi serta proses rekapan data dari absensi membutuhkan banyak waktu dikarenakan dosen harus menghitung satu per satu jumlah mahasiswa yang tidak hadir sebelum atau sesudah proses pembelajaran. Proses tersebut kurang efektif dan efisien dikarenakan banyaknya langkah-langkah yang harus dilakukan. Sehingga pemanfaatan perkembangan teknologi dibutuhkan guna membantu dosen dalam proses absensi yang efektif dan efisien. Tujuan penelitian ini adalah merancang dan membangun sistem informasi absensi yang menggunakan Qr Code guna memudahkan dosen dan mahasiswa/i dalam proses absensi sebelum atau sesudah memulai pembelajaran di kelas. Sistem ini dibangun menggunakan PHP, MySql, Xampp dan visual studio code. Hasil dari penelitian ini berupa pembuatan sistem informasi absensi menggunakan Qr Code pada Fakultas Ilmu Komputer dan Manajemen USTJ berbasis web yang dapat diakses oleh dosen dan mahasiwa menggunakan smartphone.
La experiencia docente influye en el uso de enfoques metodológicos ¿mito o realidad?
Authors: Rodríguez-García Alejandro , Arias-Gago Ana Rosa
Published: February 2025

Las metodologías activas son definidas como: “aquellos métodos, técnicas y estrategias que utiliza el docente para convertir el proceso de enseñanza-aprendizaje en actividades que fomenten la participación activa del estudiante y su protagonismo” (Labrador-Piquer y Andreu, 2008, p. 6). Dichas metodologías cada vez están adquiriendo mayor relevancia como consecuencia de la actual renovación pedagógica que se está comenzado a impulsar desde los centros educativos (Monereo, 2003). Además, según autores como Crisol (2012), Pérez-Pueyo (2010), y Swartz (2013) señalan que su utilización desarrolla competencialmente a los alumnos en aspectos transversales, aplicables a todos los ámbitos de la vida cotidiana. Esta aplicabilidad a diversos ámbitos se vincula a las características de este tipo de metodologías. En este sentido, Toro y Arguis (2015), y Hernández y Guárate (2017), establecen que las características que un enfoque metodológico debe de disponer para ser activo, son las siguientes: promover la creatividad, la crítica y el sentido de iniciativa y espíritu emprendedor; partir de los intereses y motivaciones de los alumnos; asociarse a una evaluación comprensiva con las características del alumnado; fundamentarse en tópicos globalizados adaptados a los intereses de los alumnos; promocionar la autonomía del alumno; organización de agrupamientos, espacios y tiempos flexibles; promoción de la colaboración y cooperación de los alumnos; el docente debe de actuar como facilitador del aprendizaje; y las Tecnologías de la información y la comunicación (TIC) han de tener un papel preponderante.
Reporteando el Desarrollo Sostenible (RDS): Estrategia de aprendizaje
Authors: Muñoz Rosales Alberto Francisco , Rueda Hernández José Fermín Enrique , Fernández Pérez Jorge Alejandro
Published: February 2025

El desarrollo sostenible es una invitación a la reflexión y a la acción consciente de los contextos, al cambio, a ver todas las partes que componen el problema. Indudablemente todos los miembros de la sociedad tienen una zona de influencia, es decir, un cierto entorno en el que le es posible generar cambios positivos y significativos a partir de una visión. Ante ello, los autores del presente capítulo, diseñaron e implementaron una estrategia integral que permita movilizar los elementos de una competencia en función de una educación para el desarrollo sostenible, teniendo como escenario de actuación a estudiantes de una institución de nivel superior. Es importante decir, el desarrollo sostenible se conceptualiza con la Organización de las Nacionales Unidas, en el informe de la comisión mundial sobre el medio ambiente y el desarrollo en 1987, cuando fungía Gro Harlem Brundtland como presidenta, en el informe nuestro futuro común, “asegurar que satisfaga las necesidades del presente sin comprometer la capacidad de las futuras generaciones para satisfacer las propias” (ONU, 1987, p.59), donde la dimensión social, ambiental y económica son sus pilares fundamentales para lograrlo. La conexión existente de la definición antes mencionada y la zona de influencia que se tiene como docentes e investigadores educativos es la estrategia de aprendizaje: RDS (reporteando el desarrollo sostenible), por el hecho de que los resultados serán alumnos que movilizarán los elementos de las competencias y contribuirá a dominar temas de su formación profesional, siguiendo una metodología nueva para esta institución, por ello, se considera innovadora y pertinente.
Metodología de aprendizaje electrónico móvil (m-learning) mediante gamificación para desarrollar competencias transversales en titulaciones universitarias
Authors: Soto Hidalgo José Manuel , Martínez Rojas María , Alonso Moral José María , Gámez Granados Juan Carlos
Published: February 2025

En el escenario del Espacio Europeo de Educación Superior (EEES) (Benito y Cruz, 2005) se plantean nuevas metodologías, tanto de evaluación como de aprendizaje, como alternativa a la clase magistral, con el fin de situar al alumno como elemento activo del proceso de enseñanza-aprendizaje. En este contexto el sistema educativo se ha centrado en el aprendizaje y el papel activo de los estudiantes, así como en la integración de las Tecnologías de la Información y la Comunicación (TIC) (Correa, 2014). Un ejemplo de integración de las TIC en el sistema educativo es el concepto de aprendizaje electrónico móvil (m-learning en inglés), el cual se puede asociar a una metodología de enseñanza y aprendizaje que facilita la construcción del conocimiento, la resolución de problemas y el desarrollo de competencias de manera autónoma y ubicua, gracias a la mediación de dispositivos móviles portables con conexión a Internet tales como teléfonos móviles, tabletas, portátiles, werables, etc. (Morales, 2014). En este sentido, el aprendizaje móvil plantea una nueva conceptualización de los modelos tradicionales de uso y aplicación de las tecnologías, una realidad con un plazo de adopción inmediato según el último informe “NMC Horizon Report: 2017 Higher Education Edition” (Becker, 2017). Es más, el uso del móvil con fines pedagógicos constituye un elemento que al ser introducido en el aula rompe con los esquemas conocidos, tal y como Tíscar Lara define el concepto m-learning: “un elemento disruptor, un ‘caballo de Troya’ que modifica las concepciones previas sobre la metodología de enseñanza, el rol del docente y del alumno, el tiempo y los espacios de aprendizaje” (Lara, 2012).
Evaluación por parte del alumnado del Aprendizaje-Servicio: formando ciudadanos críticos y transformadores
Authors: Sandín Vázquez María
Published: February 2025

El Aprendizaje-Servicio (APS) es una metodología pedagógica de alto poder formativo ya que combina en un solo proceso el aprendizaje de contenidos, competencias y valores con la realización de tareas de servicio a la comunidad (Puig, Batlle, Bosch et al., 2010). El alumnado que participa en este tipo de proyectos aprende mientras trabaja en necesidades reales del entorno, con la finalidad de mejorarlo (Puig, Batlle, Bosch, y Palos, 2007). El APS conecta íntimamente el aprendizaje con la acción en el contexto real en el que se está desarrollando, por lo que el alumnado comprende, se motiva y se implica al ver una aplicación y trasferencia real de sus nuevas competencias. Es por ello una metodología orientada a la educación para la ciudadanía, inspirada en las pedagogías activas (Batlle, 2013). Detrás del APS, hay una manera de entender el mundo, la educación, la práctica docente, el proceso de aprendizaje y la ciudadanía, que según el enfoque del APS debe ser crítica, activa y reflexiva.
Estrategias pedagógicas para facilitar la comprensión de contenidos contables a través de entornos virtuales en Argentina
Authors: Suarez Kimura Elsa Beatriz , Padín María Belén
Published: February 2025

El equipo de investigación realiza desde hace más de treinta años un seguimiento constante del avance de las tecnologías en relación directa con los sistemas de información contable y, en consecuencia, de los requerimientos de habilidades tecnológicas para el Contador Público. En esa línea, hace ya más de dos décadas, en el orden internacional y nacional se viene trabajando en la elaboración de guías de educación para Contadores Públicos que incluyen específicamente las competencias profesionales que deberían tener en el área de los sistemas de información de las organizaciones. Lo que se busca es que los futuros profesionales se formen tanto en conocimientos técnicos específicos de su área, como en habilidades tecnológicas, pues estas le serán requeridas para el buen desempeño de su trabajo. Esto requiere que, desde su formación en la Universidad, adquieran ambos tipos de conocimiento. Ello es posible, si el docente que imparte una asignatura virtual desarrolla estrategias pedagógicas apropiadas para la nueva tecnología, a fin de ayudar a los alumnos a adquirir las habilidades relacionadas con las Tecnologías de la Información, que le serán útiles dentro de su ámbito profesional en un futuro.
Effects of Social Media Use on Students Academic Achievement at University Level
Authors: Saif Ullah  , Dr Muhammad Imran  , Dr Muhammad Imran Yousuf
Published: February 2025

The rapid integration of social media into university students' lives has sparked debates about its dual role as both an educational tool and a source of distraction. This study investigates the effects of social media use on academic achievement among 410 students from six universities in Rawalpindi and Islamabad, Pakistan, using a quantitative, non-experimental design. Guided by the Technology Acceptance Model (TAM) and Bandura’s theory of academic self-efficacy, the research explores how mediating variables—including perceived usefulness, technology-enhanced learning (TEL), and academic motivation—shape this relationship. Data were collected via a validated questionnaire and analyzed using SPSS and Smart PLS. Results revealed a significant negative correlation between excessive social media use and GPA (β = -0.22, p < 0.01), with students averaging 4.6 hours daily on platforms like WhatsApp and YouTube. However, perceived usefulness of social media partially mitigated this effect (β = 0.15, p < 0.05), while academic self-efficacy strengthened engagement with TEL (β = 0.34, p < 0.001). The study underscores the importance of structured digital literacy programs and institutional policies to optimize social media’s educational potential. Educators are urged to foster self-regulation and integrate social media into curricula purposefully. These findings highlight the need for balanced, context-specific strategies to harness social media’s benefits while addressing its risks.
Intellectual Property and Innovation: A Critical Assessment of Patent Law and Economic Growth
Authors: Muhammad Hassan Shahid  , Fatima Rida Suddle  , Gohar Masood Qureshi
Published: February 2025

Patent law plays a crucial role in fostering innovation and driving economic growth by granting temporary monopoly rights to inventors. This study critically examines the effectiveness of patent law in promoting technological advancements and economic development. The research explores whether patents truly incentivize innovation or create monopolistic barriers that hinder competition and access to knowledge. It also assesses the impact of patents on developed and developing economies, highlighting the challenges of patent thickets, evergreening, and high patenting costs. Using a doctrinal research approach, this study analyzes legal frameworks, economic theories, and empirical data to evaluate the correlation between patent protection and economic growth. The findings reveal that while patents encourage research and development (R&D) in high-tech industries, they may also stifle innovation by creating barriers to entry for small businesses and restricting access to essential technologies. The study suggests that reforming patent laws—through anti-evergreening measures, simplified patenting procedures, and flexible licensing—can help strike a balance between incentivizing innovation and ensuring public access to technology. This research contributes to the ongoing debate on intellectual property rights by offering policy recommendations to optimize patent law’s role in sustainable economic growth and equitable technological progress.
Investigating the Factors Predicting the Financial Distress of Firms: A Study Based on Pakistani Firms
Authors: Muhammad Tariq  , Muhammad Hasan  , Aurangzeb Khanji  , Atif Aziz
Published: February 2025

This study tries to investigate the determinants of financial distress or bankruptcy prediction of the non-financial firms listed on the Pakistan Stock Exchange 100 Index. The study has taken a sample of 21 non-financial firms representing the cement, sugar, and textile sectors for analysis in the period spanning from 2014 to 2023. Altman's Z-score is considered as proxy for financial distress. This study applies the Panel Least Squares (PLS) approach to test the hypotheses besides the Fixed Effect (FEM) and Random Effect (REM) models. A comparative assessment of PLS, FEM, and REM was also performed in comparing the model performance. The results indicate that the liquidity, efficiency, and solvency ratios are positively associated with the financial distress measured using the Altman Z-score. On the other hand, leverage and firm size show a very important negative relationship with financial distress; this may further mean that even large firms may become distressed due to other contributing factors. Profitability, as represented by profit margins, does not show any significant impact on financial distress in this study. The study underscores the importance of using bankruptcy prediction models to enable firms to identify likely financial distresses early. Companies also need to look forward toward other factors that may cause distress and focus on if cash flow and debt management practices need improvement to meet their financial obligations efficiently.
A comparative Analysis of Quaid-e-Azam and Imran Khan: According to Speech Act Theory
Authors: Zohaib Hassan  , Noor Fatima  , Malaika Shoukat  , Laiba Razzaq
Published: February 2025

The core purpose of this article is to identify the intentions of political leaders while they have been talking about the prosperity of country. Here in this article, researcher's mainly have focused on speeches of two major political leaders of Pakistan, one is Quaid e Azam (Founder of Pakistan) and second is Imran khan (former Prime Minister of Pakistan). The researchers have analyzed linguistic choices made by Imran khan and Quaid e Azam in their speeches by applying speech act theory. The data has collected through different online websites and from subtitles of speeches of both leaders. The data has analyzed by applying speech act theory’s illocutionary speech acts which was present by J.L. Austin and John Searle which basically reveals the intentions and underlying meanings behind language or dialogues. The objective of this paper is to uncover the hidden ideologies and mindset of Quaid e Azam and Imran Khan in accordance of speeches. The difference in working of institutions of Pakistan has been discussed in this article. There Quaid e Azam had different point of view on working of institutions like judiciary, foreign policy, military, health, education and economic system of the country as well while Imran khan had other opinions about their working. Researchers have mentioned the dialogues of both leaders in which they showcase their point of view of being different.
Implementation Of Standard Minute Value (SMV) to Achieve Bra Production Target at PT Globalindo Intimates
Authors: Atsilia Shasna Aziizah , Isfianadewi Dessy
Published: February 2025

Standard Minute Value (SMV) is a method for measuring the standard time for completion of a production process in achieving production targets in accordance with a predetermined plan. In this research, analysis related to SMV was carried out at PT Globalindo Intimates, which is a garment industry manufacturing company whose products are underwear or women's underwear.  This research aims to determine the strategies and challenges in implementing SMV to achieve bra production targets. Data collection techniques were carried out using observation, interviews and documentation. Based on the research that has been carried out, the strategy used to implement SMV can be in the form of research to determine the level of difficulty in the production process and observation to see problems in the production process because each type of bra has a different level of difficulty. Factors that cause production targets to not be achieved are unplanned absences, operator skills, machine problems, and human error.