bluuebunny/crossref_metadata_2025 huggingface dataset:
A utilização da plataforma GeoGebra.org em atividades práticas de Geometria para estudantes do Ensino Fundamental
Authors: de Souza Jaime Batista , Jardim Deborah Faragó , Guimarães Patricia Baldow , Petzold Vitor Hugo , Oliveira Uany Souza , Gonçalves Alice Santos
Published: December 2024

O presente trabalho apresenta uma pesquisa qualitativa a partir de uma ação de extensão universitária. A tarefa consistiu na aplicação de atividades práticas com a utilização da plataforma de recursos de matemática dinâmica GeoGebra.org, para estudantes de 18 turmas de 7º, 8º e 9º anos do ensino fundamental, da Escola Municipal Irmã Maria Amália (EMIMA), localizada na cidade de Teófilo Otoni - MG. Os estudantes foram recebidos no ICET/UFVJM, acompanhados de seus professores, e participaram de atividades envolvendo a aplicação de conceitos de Geometria Plana com a utilização da referida Plataforma. Foi possível verificar o interesse, a motivação e a capacidade dos estudantes diante da integração dessa ferramenta pedagógica na abordagem de conteúdos matemáticos. É possível concluir que a implementação de plataformas digitais interativas, como o GeoGebra.org, pode ser uma ferramenta auxiliar no ensino, promovendo tanto a inclusão social quanto o desenvolvimento de habilidades matemáticas de forma eficaz.
Ambiente Digital Simulado de Atendimento em Telemedicina: Inovação na Educação Médica com Moodle
Authors: Cabral Luiz Fernando Ibrahim Rebello , da Silva Marcos Antonio , e Cunha Caio Silva , Lima Ramon Fraga de Souza , da Silva Marcos Alex Mendes , Pereira Anrafel Fernandes
Published: December 2024

A telemedicina, uma tecnologia emergente que tem avançado significativamente nas práticas médicas, torna-se cada vez mais relevante. Para preparar futuros médicos para os desafios de um sistema de saúde em constante evolução, a Coordenação Geral de Ensino Digital da FUSVE, em parceria com o curso de Medicina da Universidade Vassouras, desenvolveu um ambiente educacional que aproxima os alunos da prática de atendimentos digitais. A proposta é que o ambiente seja utilizado na educação médica, para ensinar o processo da consulta remota — desde o agendamento até o preenchimento do laudo médico e a solicitação de exames — permitindo que os estudantes adquiram conhecimento e pratiquem de forma correta. Explorando as potencialidades de softwares livres, como o Moodle, um ambiente amplamente utilizado no contexto educacional e agora aplicado ao ensino médico, essa iniciativa prepara os alunos para a medicina moderna, onde a tecnologia é essencial no atendimento ao paciente.
Perséfone: Um site informativo sobre métodoscontraceptivos para adolescentes
Authors: Sattler Gabrielly Vitoria , Manfrin Jéssica , Santana Rayssa M. S.
Published: December 2024

A adolescência representa uma marca importante na vida da mulher em função das inúmeras transformações fisiológicas e psicológicas que ocorrem nesta fase. Ademais, tal fase pode apresentar ainda maior complexidade quando a adolescente passa por uma gestação, inclusive trazer riscos para a mãe e para o feto. A falta de acesso a informações seguras sobre educação sexual e métodos contraceptivos é um dos fatores que contribui para agravar o problema. Diante disso, o objetivo principal deste estudo é desenvolver uma aplicação web informativa que disponibilize dados seguros e acessíveis sobre métodos contraceptivos para todas as mulheres, priorizando as adolescentes, independentemente de sua classe social. Para isso foi realizada uma pesquisa bibliográfica que serviu como base para definir as funcionalidades do site. A aplicação web está em desenvolvimento, utilizando as tecnologias JavaScript (incluindo o Node.js), HTML, CSS e MySQL. Até o momento, um protótipo inicial da aplicação web foi criada na plataforma Canva, demonstrando as interações entre a aplicação e o usuário. Também foram desenvolvidos os diagramas de caso de uso e entidade relacionamento (DER). Espera-se que a aplicação forneça informações claras e seguras sobre educação sexual e os métodos contraceptivos, promovendo a conscientização das adolescentes e auxiliando-as a conhecerem melhor seus corpos e na escolha do melhor método contraceptivo para as suas necessidades e realidades.
WIMA: An Open-Source API for efficient Image Transmission on Wireless Sensor Networks
Authors: de Sousa Janislley Oliveira , Santos Ricardo Nogueira , P. Júnior João Danilo , Lima Moysés M.
Published: December 2024

This paper explores the integration of image sensors into Wireless Sensor Networks (WSN) for Internet of Things (IoT) applications, an area currently limited by technical constraints. It introduces WSN Image API (WIMA), an open-source and adaptable API designed to unify and simulate the stages of image transmission. Developed and designed on the Contiki-NG/Cooja platform, WIMA has demonstrated its viability through simulations of use cases, validating its efficacy in supporting image transmission in WSN environments. The API offers a standardized approach for incorporating image data into WSN, addressing a significant gap in current methodologies to simulate this scenario for IoT applications. Future work will focus on deploying WIMA in real-world scenarios to evaluate and improve its image transmission capabilities.
Jogos Digitais sob a perspectiva da Engenharia de Software: um mapeamento sistemático da literatura
Authors: Morgenroth Alexssandro , Santos Marcos Ramos dos , Santander Victor Francisco Araya
Published: December 2024

A adoção dos Jogos Digitais foi amplamente utilizada para manter os estudantes engajados pedagogicamente no Ensino Remoto Emergencial (ERE). Além disso, evidenciou uma valorização exponencial em relação ao uso e desenvolvimento industrial do Jogos Digitais nas diferentes demandas de mercado. Este artigo apresenta os resultados de um Mapeamento Sistemático da Literatura (MSL) que inclui a análise de artigos sobre Jogos Digitais e a Engenharia de Software a partir de três importantes bases internacionais, nomeadamente ACM Digital Library, Scopus e Springer Link, repositórios recomendados para a realização de pesquisas na área de Engenharia de Software. A ferramenta Parsifal foi utilizada para apoiar a execução da MSL. Foram analisados os estudos primários dos anos de 2020 a 2024 (pandemia e pós-pandemia de Covid-19), tendo como fenômeno de interesse a obtenção de informações empíricas em relação à utilização de técnicas de Engenharia de Software no desenvolvimento de Jogos Digitais. Um total de 112 estudos foram indexados a partir da string de busca, dos quais 99 a partir dos critérios de inclusão e exclusão foram rejeitados e 13 foram analisados para responder às questões de pesquisa e análise dos critérios de avaliação. Analisando os dados, conclui-se que a maioria dos estudos apresentam a Engenharia de Software de forma tímida ou pontual no desenvolvimento de Jogos Digitais.
Omnis Chess: Desenvolvimento de um xadrez adaptado para Pessoas Com Deficiências Físicas dos Membros Superiores por Meio de Hardware e Software Livre
Authors: Cechim Filipe Potrich , Ganhor João Paulo , de Souza Odair Moreira
Published: December 2024

O projeto Omnis Chess busca promover a inclusão de pessoas com deficiência física nos membros superiores à prática do xadrez. Dados do IBGE mostram que 3,7% da população brasileira possui algum grau de deficiência nos membros superiores, evidenciando a necessidade do desenvolvimento de tecnologias assistivas. Conforme a Lei Nº 13.146/2015, há a garantia ao direito ao acesso igualitário a esportes e lazer. O objetivo é desenvolver um sistema autônomo capaz de reconhecer comandos de voz em português e movimentar automaticamente as peças no tabuleiro. Para isso, o sistema utiliza um microcomputador Raspberry Pi Zero 2W, bibliotecas de código aberto, como python-chess para a lógica do jogo, SpeechRecognition (online) e Vosk (offline) para reconhecimento de voz e com suporte ao modelo Kaldi. A estrutura física baseia-se em um mecanismo CoreXY, comum em impressoras CNC, controlada por motores de passo. Os resultados parciais indicam o funcionamento da integração das tecnologias online, enquanto o reconhecimento de voz offline com a biblioteca vosk integrada com um modelo Kaldi para o português precisa ser otimizado, melhorando a resposta a comandos específicos, e assim integrar o software ao protótipo físico e iniciar os testes de usabilidade e garantir que o Omnis Chess seja uma ferramenta eficaz para a inclusão social.
Avaliação de modelos de implantação de funções serverless no serviço AWS Lambda
Authors: Duessmann Gabriel , Fiorese Adriano
Published: December 2024

Com o avanço da computação em nuvem e serviços serverless, mais foco essa área vem ganhando nos últimos anos. Provedores de nuvem oferecem serviços relacionados a serverless, e em particular, a Amazon disponibiliza o AWS Lambda para a criação de funções serverless. Existem ao menos duas formas de implantá-los: através da compressão da pasta do projeto, que contém o código fonte e arquivos executáveis, em formato ZIP; e a segunda maneira na qual a aplicação e suas dependências estão em uma imagem de contêiner. Dependendo da abordagem escolhida, o desempenho, o custo e o tempo de inicialização podem variar. Levando em consideração essas métricas, este trabalho visa compará-las entre as duas abordagens de implantação mencionadas e tem como objetivo descobrir se uma das abordagens apresenta ser mais adequada do que outra. Experimentos conduzidos visando tal comparação demonstram que a criação de funções utilizando pastas compactadas apresentam vantagens, principalmente no tempo de inicialização da função quando está em modo de partida fria, e no custo.
A Engenharia de Requisitos e a Lei Geral de Proteção de Dados (LGPD): Uma Revisão Sistemática da Literatura
Authors: Elger Eduarda , Santander Victor Araya
Published: December 2024

Em setembro de 2020, a Lei Geral de Proteção de Dados (LGPD) entrou em vigor no Brasil, regulamentando o tratamento de dados em meios físicos e digitais, tanto em instituições públicas quanto privadas, com o objetivo primordial de assegurar a privacidade e os direitos individuais. Diante desse cenário, a engenharia de requisitos direciona sua atenção para a influência da LGPD nas fases iniciais do desenvolvimento de software, especialmente no âmbito dos requisitos não-funcionais (NFR). Este trabalho propõe uma abordagem baseada nas etapas de planejamento e execução de uma revisão sistemática da literatura (RSL) para analisar métodos, técnicas e estudos utilizados na engenharia de requisitos, com foco no requisito não-funcional de privacidade, visando a conformidade com a LGPD.
The Application and Limitation of IoT in Bills of Lading: Reflection on Future Technological Directions
Authors: Yang Rong Rong , Matheus Jr. Dirceu , Bianchini Calebe P.
Published: December 2024

The maritime shipping industry is increasingly using the Internet of Things (IoT) to improve the management of bills of lading, enabling real-time tracking and data sharing. However, IoT faces challenges such as technical complexity, data security risks, and high costs. This paper examines the applications and limitations of IoT in this context, highlighting areas where improvement is needed. While specific solutions are not discussed, the paper suggests that future technologies like blockchain may complement IoT, offering a direction for further research and development.
Tutor Inteligente: Machine Learning Aplicada ao Processo de Ensino e Aprendizagem da Matemática no Ensino Básico
Authors: Santos Paulo Ricardo Mesquita Rosa , Ferreira Vinícius Marques da Silva , Alves Luiz Anastácio , Boente Alfredo Nazareno Pereira , Sarto Neto João Jorge , Marinho Jean Marcos Rebello
Published: December 2024

Este artigo apresenta o desenvolvimento do Tutor Inteligente, um sistema baseado em machine learning, criado para personalizar o processo de ensino-aprendizagem da matemática no ensino básico. A metodologia adotada envolve técnicas de aprendizado de maquina para análise e adaptação do conteúdo às necessidades individuais dos alunos. O desenvolvimento do sistema segue uma abordagem incremental com metodologias ágeis (SCRUM), incluindo testes contínuos (TDD) e integração com ferramentas de avaliação em tempo real. Os resultados parciais mostram que o Tutor Inteligente fornece feedback imediato e suporte adaptativo, promovendo uma experiência de aprendizado mais eficaz e interativa para alunos com dificuldades específicas na matemática. A conclusão aponta o sistema como uma ferramenta complementar ao ensino, capaz de enriquecer o processo educacional e aumentar a retenção de conhecimento.
Um framework conceitual para criação e implementação de proteção de dados
Authors: Barkoczy Jean Fellipe , Lara Guilherme Heck , Barros Solange Duarte Palma de Sá , Knihs Everton , Silveira Ismar Frango
Published: December 2024

Este trabalho foi desenvolvido com o objetivo de expor o que é necessário criar para proteção de dados, observando um framework conceitual que atenda as normas legais de proteção de dados e privacidade. Com a busca de uma referência que englobasse os temas pesquisados, percebe-se a necessidade de instrução e suporte para navegar entre as normas legais que orientam o tema. Sendo assim, propõe-se um framework conceitual em forma de ontologia, para indicar as etapas necessárias para adequar as normas vigentes, servindo para instruir as medidas técnicas e legais necessárias para a proteção de dados.
Iniciação Científica de Estudantes do Ensino Médio Integrado Assistida por uma Trilha Digital de Aprendizagem
Authors: Zilio Rafaela da Silva , Ambrósio-Accordi Andreia , Accordi Iury de Almeida , Santini Luciane Alves , Ferraz Thales Ambrósio de Albuquerque
Published: December 2024

Este artigo detalha a criação de uma trilha digital de aprendizagem hospedada no Canva Sites que disponibiliza conteúdos utilizados pelo projeto "LABIC Viamão – Laboratório de Iniciação Cientifica para alunos do Campus Viamão". Em resposta à necessidade de complementar e personalizar o aprendizado presencial, a trilha digital oferece conteúdos interativos e personalizados, facilitando consultas em bases de dados, citação, referências bibliográficas e técnicas de escrita acadêmica. A pesquisa visa melhorar a compreensão dos tópicos abordados e proporcionar uma experiência educacional mais integrada, preparando os estudantes para serem protagonistas em sua formação científica.
Ensino Híbrido como alternativa de estudo: uma experiência na Universidade no decorrer das enchentes em Porto Alegre (RS)
Authors: Ziede Mariangela Kraemer Lenz , Picetti Jaqueline , Real Luciane Magalhães Corte
Published: December 2024

Este artigo objetiva analisar como a utilização de metodologias ativas no contexto da Educação a Distância (EaD) e do ensino híbrido contribuiu para o engajamento dos alunos de Cursos de Licenciaturas da Universidade Federal do Rio Grande do Sul no decorrer das enchentes no Rio Grande do Sul. Trata-se de um estudo de caso de duas turmas de disciplinas da Graduação que interagiram de maneira híbrida mediadas por propostas pedagógicas em que colocavam os estudantes em ação com o objeto de conhecimento
The Climate-Conflict Nexus in South and Southeast Asia
Authors: Baumann Tim
Published: December 2024

Climate change impacts will increase the risk of violent conflict breaking out by undermining the living conditions of the people affected by it. For this reason, activities that support vulnerable people’s capacity to adapt to climate change are needed. One new approach to tackling this issue is climate risk financing, which includes three layers, namely risk prevention, risk financing and risk management. The objective of this work is to answer the research question: Under which conditions can current climate risk financing instruments contribute to mitigating the potential for climate-related violent conflict in South and Southeast Asia?
X-Ray Utilization Patterns in Pediatric Musculoskeletal Trauma: Assessing Potential Overprescription
Authors: Gatto Antonio , Capossela Lavinia , Ferretti Serena , Covino Marcello , Di Sarno Lorenzo , Pansini Valeria , Chiaretti Antonio
Published: December 2024

Background: Traumatic injuries are among the leading causes of visits to the pediatric emergency department (PED). Objectives: This study aims to evaluate the pediatric approach to musculoskeletal trauma in children to determine whether the routine use of X-rays can be reduced by encouraging the use of ultrasound. Methods: This retrospective observational study included children aged 0 - 18 years admitted to the PED of the Policlinico A. Gemelli with a diagnosis of musculoskeletal trauma from January 2017 to December 2021. Patients were divided into two groups based on the presence of fractures identified through radiological examinations: "Fracture Yes" and "Fracture No." Data on X-rays performed were categorized according to the site of trauma. Results: A total of 5,972 children were enrolled. The most notable findings concern the regions of trauma. Among 1,273 patients who underwent X-rays of the hand region, 617 (48%) showed fractures, and 656 (51%) did not. Of the 744 X-rays performed for the foot region, 235 (31%) revealed fractures, while 509 (68%) were negative for fractures. In the upper limbs region, 1,334 X-rays were performed, with 1,079 (80%) identifying fractures and 255 (20%) showing no fractures. For the lower limbs region, 479 X-rays were conducted, 204 (42%) of which revealed fractures, while 275 (58%) were negative for fractures. All these results demonstrated statistically significant differences (P < 0.05). Conclusions: Despite the limitations of the study's retrospective design and its single-center setting, the findings highlight a high prevalence of X-rays in the hand and upper limb regions, often with positive results. In contrast, radiography of the lower limbs and feet frequently yielded negative findings, suggesting potential overuse. Future research should investigate the clinical utility of musculoskeletal ultrasound as an alternative imaging modality to minimize unnecessary radiation exposure in pediatric patients.
Genotyping and Antifungal Susceptibility Testing of Aspergillus flavus Isolated from Clinical Specimens
Authors: Dehqan Leila , Nasrollahi Omran Ayatollah , Taghizadeh Armaki Mojtaba , Hashemi Karoui Masoud , Mahdavi Omran Saeid
Published: December 2024

Background: After Aspergillus fumigatus, A. flavus is the second leading cause of invasive and non-invasive aspergillosis. These fungi are of significant epidemiological importance in provinces with dry and hot climates. Objectives: In the present study, antifungal susceptibility testing (AFST) and genotyping of sixty-five A. flavus clinical isolates originating from patients in Mazandaran and Tehran were performed. Methods: Antifungal susceptibility testing of 65 clinical isolates of A. flavus was conducted against amphotericin B (AMB), itraconazole (ITR), voriconazole (VOR), posaconazole (POS), isavuconazole (ISA), luliconazole (LUL), lanoconazole (LAN), and 5-fluorocytosine according to the Clinical Laboratory Standards Institute (CLSI) method (M38-A2). The minimum inhibitory concentrations (MICs) were determined for each antifungal drug against all strains. Additionally, microsatellite typing using six variable number tandem repeat (VNTR) markers was performed to assess the genetic diversity and potential relationships among the clinical strains. Results: Luliconazole had the lowest geometric mean MIC (0.020 μg/mL), followed by LAN (0.021 μg/mL), POS (0.089 μg/mL), ISA (0.115 μg/mL), ITR (0.220 μg/mL), VOR (0.244 μg/mL), AMB (0.870 μg/mL), and 5-fluorocytosine (58.76 μg/mL). Microsatellite typing revealed sixty-five distinct sequence genotypes. Statistically, there was no significant relationship between genotypes and AFST profiles (P ≥ 0.05). Conclusions: Luliconazole and lanoconazole demonstrated the greatest in vitro activity among all tested antifungals. However, most A. flavus strains exhibited reduced sensitivity to AMB. Microsatellite genotyping indicated no genetic similarity among the clinical strains, revealing high genetic diversity among A. flavus isolates obtained from clinical samples.
Study of Effective Factors and Policies on the Development of Health Tourism in Iran as a Developing Country
Authors: Keivan Hosseiny Asghar , Aryakian Zahra , Aryakian Zeynab
Published: December 2024

Background: Medical tourism, a byproduct of globalization, involves patients traveling beyond their national borders for healthcare. While this trend is prominent in developed countries, developing nations like Iran can capitalize on it for economic gains. Objectives: This study explores the potential and prerequisites for the advancement of medical tourism in Iran, a developing country with significant potential in health services and a need for the development of health tourism to foster further economic growth. Methods: The target group for this study includes Iranian hospitals. The methods used are "Data Collection and Analysis". First, data were gathered from official health and tourism sources through interviews. Second, relevant factors were identified and analyzed qualitatively through a systematic review of related literature. Results: The study found that beyond the quality of medical services, cultural attributes, legal frameworks, and the tourism appeal of historical sites significantly impact the growth of medical tourism. Key opportunities for Iran's medical tourism include a high number of advanced medical centers, cost-effective and high-quality healthcare, and the allure of historical and natural tourist attractions. However, challenges such as the absence of a centralized coordinating body, limited private sector involvement, and inadequate oversight pose constraints. This study aimed to answer questions about the requirements for medical tourism development and the limitations of its achievement in developing countries. Conclusions: To enhance medical tourism in Iran, it is essential to adopt a "multifaceted approach" that integrates economic, legal, cultural, and service quality considerations. This approach should improve infrastructure, such as healthcare accommodations, and encourage the participation of private healthcare providers. Furthermore, strategic development in these areas will not only contribute to Iran's economic growth but also enhance its global reputation as a hub for high-quality healthcare services.
Delay-sensitive Quality of Service Routing with Integrated Admission Control for Wireless Mesh Network
Authors:   Department of Computer Science and Engineering, S.G. Balekundri Institute of Technology, Belagavi, India, Bhojannawar Satish S. , Managalwede Shrinivas R. , Cruzado Carlos F.
Published: December 2024

Wireless mesh networks (WMNs) extend and improve broadband Internet connectivity for the end-users roaming around the edges of the wired network. Amid the explosive escalation of users sharing multimedia content over the Internet, the WMNs need to support the effective implementation of various multimedia applications. The multimedia applications require assured quality of service (QoS) to fulfill the user requirements. The QoS routing in WMNs needs to guarantee the QoS requirements of multimedia applications. Admission control (AC) is the primary traffic control mechanism used to provide QoS provisioning. AC admits a new flow only if the QoS requirements of already admitted flows are not violated, even after the admission of a new flow. We propose a new QoS routing protocol integrated with AC called Delay-Sensitive QoS Routing with integrated Admission Control (DSQRAC) to control the admission of delay-sensitive flows. A delay-aware cross-layer routing metric is used to find the feasible path. DSQRAC is implemented using ad-hoc on-demand distance vector (AODV) routing protocol, where a delay-sensitive controlled flooding mechanism is used to forward the route request packets. In the proposed work, we adjust/reassign the channels to aid the QoS routing to increase the likelihood of accepting a new flow. The simulation results show that the performance of the proposed QoS routing protocol is better than the existing schemes.
Two-factor Mutual Authentication with Fingerprint and MAC Address Validation
Authors:   Department of Computer Science and Engineering, Karunya Institute of Technology and Sciences, Coimbatore, Tamil Nadu, India, Jolin J.S. , Theophilus A. , Kathirvel A.
Published: December 2024

Mobile Ad hoc NETworks (MANET), unlike typical wireless networks, may be used spontaneously without the need for centralized management or network environment. Mobile nodes act as mediators to help multi-hop communications in such networks, and most instances, they are responsible for all connectivity tasks. MANET is a challenging endeavor because these systems can be attacked, which can harm the network. As a result, security concerns become a primary factor for these types of networks. This article aims to present an efficient two-factor smart card-based passcode authentication technique for securing legitimate users on an unprotected network. This scheme enables the password resetting feature. A secured mechanism for sharing keys is offered by using the hash function. We present a new two-factor mutual authentication technique based on an entirely new mechanism called the virtual smart card. Compared to authentication, the proposed method has fewer computation processes but is more time efficient since it is based on a hash function. Additionally, this approach is resistant to most attacker behaviors, such as Mutual authentication, Gateway node bypassing attacks, DoS attacks, replay attacks, Man in the middle attacks, and stolen smart device attacks. Experimental results validate the efficiency of this scheme, and its security is also analyzed.
An Efficient Optimized Neural Network System for Intrusion Detection in Wireless Sensor Networks
Authors:   Department of CSE, National Institute of Technology, Karnataka, India, Sanshi Shridhar , Vatambeti Ramesh , V. Revathi , Rahman Syed Ziaur
Published: December 2024

In the realm of wireless network security, the role of intrusion detection cannot be overstated in identifying and thwarting malicious activities within communication channels. Despite the existence of various intrusion detection system (IDS) approaches, challenges persist in terms of accurate classification and specification. Consequently, this article introduces a novel and innovative approach, the African Vulture-based Modular Neural System (AVbMNS), to address these issues. This research aims to detect and categorize malicious events in wireless networks effectively. The methodology begins with preprocessing the dataset and extracting relevant features. These extracted features are then subjected to a novel training technique to enhance the detection and classification of network attacks. The integration of African Vulture optimization significantly enhances the detection rate, leading to more precise attack identification. The research's effectiveness is demonstrated through validation using the NSL-KDD dataset, with impressive results. The performance analysis reveals that the developed model achieves a remarkable 99.87% detection rate and 99.92% accuracy when applied to the NSL-KDD dataset. Furthermore, the outcomes of this novel model are compared with existing approaches to gauge the extent of improvement. The comparative assessment affirms that the developed model outperforms its counterparts, underscoring its effectiveness in addressing the challenges of intrusion detection in wireless networks.
Anti-jamming and Power Minimization Interference Nulling in Uplink MIMO-NOMA Technique
Authors:   School of Electronics and Communication Engineering at GM University, Davangere, India, P. G. Suprith , Ahmed Mohammed Riyaz , Sathiyanarayanan Mithileysh
Published: December 2024

Non-orthogonal Multiple Access (NOMA) provides use of the power domain to boost system efficiency in the spectrum. This letter explores the use of a new transceiver design and non-orthogonal multiple access (NOMA) for MIMO uplinks. The overall energy use can be reduced while still meeting individual rate requirements by utilizing a new NOMA implementation scheme with group interference cancellation. Jamming attacks can target NOMA communication. MIMO technology is used to implement anti-jamming regulations in NOMA systems. While subsequent interference cancellation utilized to get rid of between groups interference, interference nulling at the transmitters and equalizers at the jointly designed receivers for improved power system efficiency. Where the transmitter is side, interference nulling techniques have been developed. By using the above technique, the total power consumption (dBm) which it required which it is less when compare to traditional technique like orthogonal multiple access (OMA). The outcomes of the simulation show that, in comparison to both signal alignment NOMA and orthogonal multiple-use communication, the proposed NOMA scheme typically requires less power.
Intelligent Identification of Cryptographic Ciphers using Machine Learning Techniques
Authors:   Department of Computer Science and Technology, Indian Institute of Engineering Science and Technology, Shibpur, Howrah, 711103, India, Sikdar Subinoy , Kule Malay
Published: December 2024

This research work demonstrates cipher-type identification methods using machine learning algorithms. Cipher-type identification is a recent research interest to do better cryptanalysis of an encryption algorithm in a minimal time. Along with the increased security issues, obfuscation is being used with encryption algorithms to keep them hidden. This is when the ciphertext identification challenge came into play. The ciphertext classification challenge was performed using both image processing and natural language processing methods. For image processing purposes, CNN was utilized; whereas text-CNN, transformers and BERT models were used as natural language processing tools. In order to train the proposed machine learning based classification models, two types of datasets were generated: image data and text data. This study compares the experimental outcomes derived from various architectural CNN, Transformer, and BERT models. We also present a comparative study of our research work with another research works which are done in the recent past. The proposed BERT model is found to be the most efficient model for the correct classification of ciphertext over other transformer and CNN-based classification models. This work will surely help the cryptanalyst to perform cryptanalysis of an encryption algorithm in a minimal time.
Enhancing Drug Recommender System for Peptic Ulcer Treatment
Authors:   Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria, Omodunbi Theresa O. , Alilu Grace E. , Obohwemu Kennedy O. , Ikono Rhoda N.
Published: December 2024

Drug Recommender Systems (DRS) streamline prescription process and contribute to better healthcare. Hence, this study developed a DRS that recommends appropriate drug(s) for the treatment of an ailment using Peptic Ulcer Disease (PUD) as a case study. Patients’ and drug data were elicited from MIMIC-IV and Drugs.com, respectively. These data were analysed and used in the design of the DRS model, which was based on the hybrid recommendation approach (combining the clustering algorithm, the Collaborative Filtering approach (CF), and the Knowledge-Based Filtering approach (KBF)). The factors that were considered in recommending appropriate drugs were age, gender, body weight, allergies, and drug interactions. The model designed was implemented in Python programming language with the Flask framework for web development and Visual Studio Code as the Integrated Development Environment. The performance of the system was evaluated using Precision, Recall, Accuracy, Root Mean Squared Error (RMSE) and usability test. The evaluation was carried out in two phases. Firstly, the CF component was evaluated by splitting the dataset from MIMIV-IV into a 70% (60,018) training set and a 30% (25,722) test set. This resulted in a precision score of 85.48%, a recall score of 85.58%, and a RMSE score of 0.74. Secondly, the KBF component was evaluated using 30 different cases. The evaluation for this was computed manually by comparing the recommendation results from the system with those of an expert. This resulted in a precision of 77%, a recall of 83%, an accuracy of 81% and an RMSE of 0.24. The results from the usability test showed a high percentage of performance of the system. The addition of the KBF reduced the error rate between actual recommendations and predicted recommendations. So, the system had a high ability to recommend appropriate drug(s) for PUD.
Active Light Weight Recommendation System for Social Networking Analysis Using a Novel Classifier Algorithm
Authors:   Department of Computer science, Kristu Jayanti college, Autonomous Bengaluru, Karnataka, India, Prakash K. , Sudharsan M.
Published: December 2024

The most popular way for people to share information is through social media. Several studies have been conducted using ML approaches like LSTM, SVM, BERT, GA, hybrid LSTM-SVM and Multi-View Attention Networks to recognize bogus news MVAN. Most traditional systems identify false news or true news exclusively, but discovering kind of false information and prioritizing false information is more difficult, and traditional algorithms offer poor textual classification accuracy. As a result, this study focuses on predicting COVID-19-related false information on Twitter along with prioritizing types of false information. The proposed lightweight recommendation-system consists of three phases such as preprocessing, feature extraction and classification. The preprocessing phase is performed to remove the unwanted data. After preprocessing, the BERT model is used to convert the word into binary vectors. Then these binary features are taken as the input of the classification phase. In this classification phase, a 4CL time distributed layer is introduced for effective feature selection to remove the detection burdens, and the Bi-GRU model is used in the classification phase. Proposed-method is implemented in Mat lab software and is carried out several performance-metrics, and there are three different datasets used for validating its performance. Proposed model's total accuracy is 97%, specificity is 98%, precision is 95%, and the error value is 0.02, demonstrating its effectiveness over current methods. The proposed social media research system can accurately predict false information, and recognized news may be offered to the user such that they can learn the truth about news on social media.
Comparative Analysis of LSTM Variants for Stock Price Forecasting on NSE India: GRU's Dominance and Enhancements
Authors:   Smt Kashibai Navale College of Engineering, SPPU Pune, India, Kolambe Milind , Arora Sandhya
Published: December 2024

The intricate realm of time series prediction using stock market datasets from the NSE India is delved into by this research. The supremacy of LSTM architecture for forecasting in time series is initially affirmed, only for a paradigm shift to be encountered when exploring various LSTM variants across distinct sectors on the NSE (National Stock Exchange) of India. Prices of various stocks in five different sectors have been predicted using multiple LSTM model variants. Contrary to the assumption that a specific variant would excel in a particular sector, the Gated Recurrent Unit (GRU) emerged as the top performer, prompting a closer examination of its limitations and subsequent enhancement using technical indicators. The ultimate objective is to unveil the most effective model for predicting stock prices in the dynamic landscape of NSE India.
Ranking of Machine Learning Algorithms Used in Disease Prediction: A Review-based Approach
Authors:   Department of Computer Applications, Kalasalingam Academy of Research and Education, Krishnankoil – 626126, Tamilnadu, India, Subramanian Shunmuga Priya , Duraipandian Amuthaguka
Published: December 2024

There are remarkable improvements in the healthcare sector particularly in patient care, maintaining and protecting the data, and saving administrative and operating costs, etc. Among the various functions in the healthcare sector, disease diagnosis is considered as the foremost function because it saves a life at the correct time. Early detection of diseases helps in disease prevention, letting the patients get vigorous and effective treatment and saving their lives. Several techniques were suggested by the researchers for disease prediction. Many literatures have been witnessed on disease prediction. This article reviews several articles systematically and compares various machine learning (ML) algorithms for disease prediction, including the Random Forest (RF), Naive Bayes (NB), Decision Tree (DT), Support Vector Machine (SVM), and Logistic Regression (LR) algorithms. A thorough analysis is presented based on the number of publications year-wise, disease-wise, and also based on the performance metrics. This review thoroughly analyzes and compares various ML techniques applied in disease prediction, focusing on classification algorithms commonly employed in healthcare applications. From the systematic review, a multi objective optimization method named Grey Relational Analysis (GRA) is used to rank the ML algorithms using their performance metrics. The results of this paper help the researchers to have an insight into the disease prediction domain. Also, the performance of various ML algorithms aids the researchers to choose a better methodology to predict a disease.
Performance Evaluation of Fake News Detection Models
Authors:   Department of Computer Science and Engineering, Obafemi Awolowo University, Ile-Ife, Nigeria, Olagunju Afeez Ayomide , Awoyelu Iyabo Olukemi
Published: December 2024

The rapid spread of misinformation on social media platforms, especially Twitter, presents a challenge in the digital age. Traditional fact-checking struggles with the volume and speed of misinformation, while existing detection systems often focus solely on linguistic features, ignoring factors like source credibility, user interactions, and context. Current automated systems also lack the accuracy to differentiate between genuine and fake news, resulting in high rates of false positives and negatives. This study investigates the creation of a Twitter bot for detecting fake news using deep learning methodologies. The research assessed the performance of BERT, CNN, and Bi-LSTM models, along with an ensemble model combining their strengths. The TruthSeeker dataset was used for training and testing. The ensemble model leverages BERT's contextual understanding, CNN’s feature extraction, and Bi-LSTM’s sequence learning to improve detection accuracy. The Twitter bot integrates this ensemble model via the Twitter API for real-time detection of fake news. Results show the ensemble model significantly outperformed individual models and existing systems, achieving an accuracy of 98.24%, recall of 98.14%, precision of 98.42%, and an F1-score of 98.24%. These findings highlight that combining multiple models can offer an effective solution for real-time detection of misinformation, contributing to efforts to combat fake news on social media platforms.
Das Verhältnis zwischen künstlerischem Prototyp und individuellem Ausdruck im Werk eines Barockbildhauers am Beispiel der Kreuzigungsgruppe
Authors: Pötzl-Malíková Mária
Published: December 2024

The present contribution is dedicated to one of the popular Baroque depictions of the Crucifixion, for which it can be assumed that we know its original typological pattern. This is a gilded relief attributed to Guglielmo della Porta (1500/1510–1577), from the property of King Philip II of Spain, located in the Escorial. The work soon became wellknown in central Europe as well, and in depictions of the Crucifixion its figures of the Virgin Mary and St John the Evangelist were then imitated for a long time and often. They also became a model for the young Anthonis van Dyck (1599–1641) in his early altarpiece on this subject. Van Dyck's "more modern" take on the original late-Renaissance model was then significant for the further development of this prototype. The work is then devoted to transformations in the understanding of both figures over the course of almost two centuries, during which, while their basic concept – especially their characteristic gestures – remained the same, the personality of the executing artist as well as the milieu and time in which the works were created manifested themselves. The ending of the Baroque also meant the end of the use of this typological pattern.
New Breakaway Parties in Slovakia: Exploring Intra-party Democracy Shifts
Authors: Cirhan Tomáš , Malý Michal
Published: December 2024

Many new parties are electorally succeeding across European party systems, including in post-communist countries. This is especially true in Slovakia, where it is accompanied by another very specific phenomenon, which in our perspective defines recent parliamentary elections – the prevalence of new breakaway parties. These newly formed parties created by splitting from parliamentary parties are now competing alongside them in early parliamentary elections. The 2020-2023 period, in addition to seeing the fall of governments, and a general political crisis and instability, was also characterized by frequent party factionalism. During this period, turbulent development within SMER-SD, ĽSNS and OĽaNO translated into the formation of three new parties – HLAS-SD, Republika, and the Democrats, which represent our case studies. The aim of our paper is to analyse how these new breakaway parties differ from their original parties organizationally, in the processes associated with intra-party democracy (IPD). We empirically explore their leadership selection, candidate selection and membership policies. The existing data (based on the Populism and Political Parties Database) indicate that their three parent parties are highly personalized with low IPD. The findings of our comparative analysis reveal that the new breakaway parties have incorporated more transparent approaches to intraparty processes compared to their parent parties. However, concerning candidate selection, they have not embraced greater inclusiveness than the parties they originated from. Overall, despite a noticeable trend towards intraparty depersonalization, the opportunity for a broader membership base to participate in the decision making process remains largely unrealized.
Success or Failure of a Newcomer? The Hlas-SD Party as a New Player in the Slovak Party System
Authors: Hynčica Pavel , Šárovec Daniel
Published: December 2024

This article is an analysis of the establishment and subsequent role of the HLAS-Social Democracy (HLAS-SD) party on the Slovak political scene with a focus on its position in the system of cooperative-competitive interactions in the early elections to the National Council of the Slovak Republic in September 2023. First, it examines the new party in the broader context of the emergence of new political parties generally, which has been a long-term characteristic of the formation and development of the Slovak political system. Second, it investigates the ideological programmatic orientation of the party and its position in the scheme of cooperative-competitive interactions and cleavages in Slovak politics over the last three years. HLAS-SD represents a particular form of Slovak social democracy and, with this ideological orientation, faces competition not only from political parties of a different orientation but also from the programmatic sister party SMER-SD. Finally, the article maps the development of electoral support for HLAS-SD as captured by regular opinion polls and shown by the results of recent elections. Shortly after its establishment, HLAS-SD became for a time preferentially the most supported political entity, but later its electoral strength declined significantly. In this case study we analyse the party positions following the elections and, considering all three mentioned dimensions, explore the development of electoral support for HLAS-SD and its subsequent role in the party system.
The Art of Self-selection or the Intervention of the Voters? The 2023 Election and the Shifting Social Bias of Slovak Parliamentary Elites since 2006
Authors: Bakke Elisabeth
Published: December 2024

Recent research has shown a trend towards more participatory nomination procedures in new as well as more established parties. However, in Slovakia most politically relevant parties have equally centralised, leadership dominated, and exclusive candidate selection modes. In the first part of the article I draw on the elite literature to investigate cross-party variation in the social bias of parliamentary elites since 2006. Using the 2023 election as a point of departure, I go on to assess how representative MPs are of their own voters, and why social bias varies across parties despite their similar selection modes. The analysis demonstrates that the impact of the selection mode as well as of voter preferences is contingent on the nomination practices of the individual parties. I found strong elements of self-selection in nearly all parties: the members of the presidium nominated themselves, and the composition of the parliamentary elites thus to a considerable extent reflects who the presidium members are. The influence of the voters is limited, because they tend to confirm the priorities of the selectorates; however, in the case of the four smallest parties in 2023, preference voting to some extent mitigated the effect of self-selection. The main drivers of preference voting were the idiosyncratic nomination practice of Ordinary People, and the presence of organised groups and parties on the list (informal alliances).
Bytí v minulosti : vojenský reenactment perspektivou divadelních a performančních studií
Authors: Dolanová Barbora , Kubina Lukáš
Published: December 2024

Studie se zabývá kulturním fenoménem vojenských reenactmentů, širší veřejnosti známým především díky populárním ukázkám tzv. bitevních rekonstrukcí. Tento fenomén byl donedávna kvůli svému divadelnímu charakteru považován za historiograficky nebo epistemologicky nerelevantní. Autoři využívají napětí mezi tělesností a minulostí jako příležitost k interdisciplinárnímu výzkumu vojenského reenactmentu, prezentují jej jako spleť komplexních činností a nahlížejí na něj z různých perspektiv humanitních a sociálních věd. Cílem autorů je seznámit čtenáře s komplexitou tohoto fenoménu a vytyčit některé klíčové otázky týkající se reenactmentu, které mohou být zodpovězeny s využitím přístupů divadelních a performančních studií.