One of the most crucial measures to maintain data security is the use of cryptography schemes and digital signatures built upon cryptographic algorithms. The resistance of cryptographic algorithms against conventional attacks is guaranteed by the computational difficulties and the immense amount of computation required to them. In the last decade, with the advances in quantum computing technology and the realization of quantum computers, which have higher computational power compared to conventional computers and can execute special kinds of algorithms (i.e., quantum algorithms), the security of many existing cryptographic algorithms has been questioned. The reason is that by using quantum computers and executing specific quantum algorithms through them, the computational difficulties of conventional cryptographic algorithms can be reduced, which makes it possible to overcome and break them in a relatively short period of time. Therefore, researchers began efforts to find new quantum-resistant cryptographic algorithms that would be impossible to break, even using quantum computers, in a short time. Such algorithms are called post-quantum cryptographic algorithms. In this article, we provide a comprehensive review of the challenges and vulnerabilities of different kinds of conventional cryptographic algorithms against quantum computers. Afterward, we review the latest cryptographic algorithms and standards that have been proposed to confront the threats posed by quantum computers. We present the classification of post-quantum cryptographic algorithms and digital signatures based on their technical specifications, provide examples of each category, and outline the strengths and weaknesses of each category.

This paper investigates the impact and implementation of Intelligent Tutoring Systems (ITS) on enhancing educational outcomes for engineering students at the Universidad Nacional del Centro del Perú. The model emphasizes the role of ITS in improving academic achievement, student satisfaction, and engagement, considering critical dimensions like emotional attitude, cognitive receptivity, and reflective strategy. Using SmartPLS for data analysis and an application developed in Flutter, the study demonstrates that ITS can positively influence student emotion and performance. Reliability metrics confirm robustness, with Cronbach's alpha values between 0.76 and 0.876 and AVE scores above 0.7. Predictive power is supported by R-squared values of 0.746 for student emotion and 0.723 for ITS impact on academic performance. Path coefficients underscore significant relationships, such as ITS influence on emotional engagement (0.549) and academic satisfaction (0.384). Findings suggest that integrating ITS with emotional and cognitive dimensions can foster higher academic satisfaction and achievement.

In recent years, the adoption of advanced machine learning techniques has revolutionized approaches to solving complex problems, such as identifying occurrences of forest fires. Among these techniques, the use of Convolutional Neural Networks (CNNs) combined with ensemble methods is particularly promising. To investigate the feasibility of detecting fires using video streams from Unmanned Aerial Vehicles (UAVs), the lightweight CNN architecture MobileNetV2 was utilized for real-time detection. Several experiments were conducted on the DeepFire dataset, which comprises an equal number of images with and without fire, to evaluate MobileNetV2's performance. Notably, the architecture's linear bottlenecks and the efficient use of inverted residuals ensure high accuracy without compromising on feature extraction capabilities. For a comprehensive assessment, MobileNetV2 was benchmarked against other models, including DenseNet121, EfficientNetV2S, and VGG16. Accuracy was enhanced by averaging predictions through methods such as voting or summing results. As documented in the literature, MobileNetV2 consistently outperforms other architectures in computational efficiency and provides an excellent balance between efficiency and the quality of learned features over multiple epochs. This study underscores the suitability of MobileNetV2 for real-time applications on drones, particularly for the detection of forest fires in resource-constrained environments. The results show that MobileNetV2 achieves the highest accuracy (0.994), sensitivity (0.994), and specificity (0.998) among the tested models, with low standard deviations across all metrics. In contrast, EfficientNetV2S exhibited the lowest accuracy and sensitivity, both at 0.779, with a specificity of 0.829. The ensemble (Sum) method achieved an average accuracy of 0.989, sensitivity of 0.989, and specificity of approximately 0.988. Therefore, MobileNetV2 not only delivers the highest accuracy and stability but also demonstrates that the choice of ensemble method significantly affects the results.

The study aimed to examine the impact of artificial intelligence on the development of electronic financial services. The population of the study involves employees from Jordanian commercial banks distributed across branches and the general administration. The researcher used a survey as the study instrument to collect data from the study sample, with 356 surveys distributed via a link. The Statistical Package for the Social Sciences (SPSS) was used to analyze the data. The results showed an impact of using artificial intelligence on the development of electronic financial services in Jordanian commercial banks. One of the prominent recommendations was for the management of commercial banks to keep pace with the advancements and developments in artificial intelligence and the expert systems environment by providing advanced operating and storage systems to keep up with the developments in electronic financial services.

This study investigates the impact of cross-Border E-commerce development on China’s foreign trade. The software SPSS is used to calculate the value of each independent variable CBEC transaction volume, business infrastructure, professional talents, and development potential, and the software STATA version 18 is used to perform all the regression analyses. The findings reveal that efficient CBEC business infrastructure, including electronic payments, logistics, and digital support systems advancements, significantly enhances trade facilitation. Additionally, developing and cultivating professional CBEC talents are critical in sustaining trade growth, though there remains a significant talent gap in high-end, composite skills. Furthermore, the study highlights the immense potential of CBEC to broaden trade channels, improve global competitiveness, and foster innovation in small and medium-sized enterprises (SMEs). The analysis indicates steady growth in CBEC transactions and infrastructure, alongside an increasing internet penetration rate, supporting the sector's expansion. The study concludes with recommendations for policymakers and businesses, emphasizing the need to enhance infrastructure, cultivate professional talents, and strengthen market potential to ensure sustainable CBEC development and boost foreign trade. These insights provide a comprehensive understanding of the mechanisms CBEC influences foreign trade, offering a valuable reference for future research and policy formulation.

The rapid advancement of drone technology has expanded their applications across various sectors, necessitating robust real-time decision-making systems. Traditional algorithms often falter in dynamic and unpredictable environments. This paper introduces a fuzzy logic-based approach to enhance the decision-making capabilities of autonomous drones. Utilizing Monte Carlo simulations, the proposed model was evaluated through three distinct experiments involving 300, 600, and 950 scenarios respectively. The first experiment demonstrated an obstacle avoidance efficiency of 82.00%, an 8.00% reduction in energy consumption, a decision accuracy of 95.33%, and a mission success rate of 79.33%. The second experiment showed an avoidance efficiency of 82.50%, maintaining the energy consumption reduction at 8.00%, with a decision accuracy of 95.83% and a mission success rate of 78.33%. The third experiment achieved an avoidance efficiency of 82.11%, with an 8.00% reduction in energy consumption, a decision accuracy of 95.26%, and a mission success rate of 78.31%. These results highlight the superior performance of fuzzy logic in real-time decision-making for autonomous drones compared to traditional methods.

The field of online pharmacies is expanding rapidly and has become a crucial component in delivering pharmaceutical services across Saudi Arabia. This study aims to explore the factors influencing the adoption of online pharmacies by the Saudi population, utilizing an enhanced version of the Unified Theory of Acceptance and Use of Technology (UTAUT) framework. This study employed a cross-sectional design, utilizing an online questionnaire that was pre-validated and shared via social media channels between August 2024 and October 2024. The study focused on Arabic-speaking individuals aged >18 years. The gathered data were examined through structural equation modeling (SEM) using AMOS software (v.22.0). The study found that the UTAUT model demonstrates strong applicability in explaining the adoption of online pharmacies, accounting for 62.4% (R² = 0.624) of the variance in behavioral intention. Among the key factors, effort expectancy (p < 0.001) emerges as the most influential predictor of behavioral intention, followed by facilitating conditions (p 0.05) do not have a statistically significant impact on behavioral intention. The study results would help formulate more effective strategies for establishing online pharmacy operations in developing nations like Saudi Arabia. This study contributes to enhancing the traditional UTAUT model through the integration of additional factors such as health literacy, personal innovativeness, perceived risk, and perceived trust. These variables introduce new dimensions to the existing literature on online pharmacies.

Social commerce is an effective instrument for enterprises aiming to expand their customer base and enhance revenues. By mastering the implementation of social media platforms (SMPs) and surmounting the accompanying hurdles, brands may achieve significant achievements in social commerce. The article investigates the impact of social commerce information sharing (SCIN) on purchase intention and perceived risk in Turkey. This examines the influence of SCIN on customer relationship quality (CRQ) dimensions, including brand trust, commitment, and satisfaction. The study precisely intends to investigate the mediating of CRQ dimensions in the relationship between SCIN and purchase intention. The study also examines the mediator role of perceived risk in the relationship between SCIN and purchase intention. Also, the study examines how online reviews moderate the relationship between SCIN and customer outcomes such as purchase intention and perceived risk. The current study employs a sample of 314 participants from Turkey to explore the relationship between SCIN, brand trust, commitment, satisfaction, purchase intention, and perceived risk. The proposed conceptual model is tested using the Structural Equation Modeling-AMOS statistical approach. The results show that SCIN strongly predicts perceived risk, purchase intention, and CRQ dimensions, such as brand trust, commitment, and satisfaction. Furthermore, the study reveals that perceived risk does not directly mediate the relationship between SCIN and purchase intention. Instead, it confirms that purchase intention is a significant consequence of CRQ dimensions and perceived risk. The results also indicate that online reviews do not moderate the relationship between SCIN and customer outcomes, such as perceived risk and purchase intention. In summary, this study underscores the pivotal role of SCIN in influencing the decision-making process of Turkish customers, particularly in the context of making purchases. The findings carry significant practical implications for marketers of SMPs aiming to influence Turkish consumers, providing valuable insights to enhance their strategy in the Turkish market.

In the rapidly evolving landscape of higher education, Social media marketing (SMM) has evolved a critical factor in shaping brand perception (B.P.) and the decision-making process of prospective students in India. This paper intends to explore the intricate dynamics among Social media (S.M.), influencer marketing, and the selection of higher academic institutes (HEIs), focusing on understanding how these factors shape students' perceptions. We conducted this research on 560 students, who represented the research's population. SEM-PLS was applied to analyze the data and acquire procedures. Surveys on the Internet were used. Employing exogenous/endogenous elements to create sequences, the SEM approach examines causal associations among elements. It provides solutions to research into causation in dimensional and structural frameworks. According to the research's findings, selecting HEI is positively impacted by SMM initiatives. The aspects of SMM activities (electronic word-of-mouth (eWOM), personalization, interaction, and trendiness) affect the HEI selection. In addition, personalization and two have an impact on perceptions of the brand. Understanding and utilizing the efficacy of S.M. and influencer marketing will be crucial for HEIs looking to draw in and hold on to potential students as the higher education environment keeps evolving in the age of digitization.

In a context where ICTs are indispensable elements for the development of business activities, it is necessary to know their influence on the internal improvement of processes. This research seeks to establish the influence of ICTs on the competitive advantage of micro-enterprises in Huancayo 2024. Research developed under a basic type study, has a quantitative approach with a correlational and cross-sectional level, the sample was made up of 59 entrepreneurs in the bakery sector in the province of Huancayo. Data analysis and processing was carried out using structural equations based on PLS. The study obtained the following results: a Sperman 's Rho correlation coefficient of 0.821 with a significance level of ,000 which shows a high and positive degree of influence between ICTs and competitive advantage as well as its different dimensions Level of use, alignment of use and training; Likewise, the general hypothesis is accepted, which establishes that there is a significant relationship between Information and Communication Technology ( ICTs ) and the competitive advantage in SMEs in the pastry sector - Huancayo 2024.