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Empowering Grade One Struggling Readers: The PAS and Multimedia Approach to Reading Intervention Success
Full text linkThe current study investigated the impact of Phonic Analysis and Synthesis (PAS) combined with a Multimedia Approach on the reading proficiency of first-grade poor readers at the Mindanao State University-Integrated Laboratory School (MSU-ILS). The program's September 2023 launch primarily focused on making it easier for beginner readers to overcome their reading difficulties, achieved through a combination of systematic phonics instruction and various multimedia resources. The intervention focused on both phoneme segmentation and synthesis, combining the practices of decoding and word recognition with watching videos, listening to audio materials, and using digital learning tools. A pre-test–post-test research design was employed to evaluate changes in spelling, vocabulary, and reading comprehension. The pre-tests were conducted in the first quarter, while the post-tests took place in the fourth quarter of the school year. Through statistical analysis, it was determined that there was a significant difference between the mean scores of the pre-test and post-test (p < .05), indicating a notable improvement in the children's reading skills after they underwent the intervention. The results suggest that the PAS method can be highly effective in teaching young children the fundamentals of reading when combined with multimedia instruction. This research contributes to the existing body of knowledge by demonstrating that reading interventions based on phonics, combined with various instructional modes, can be highly effective. Additionally, it emphasizes that early literacy development should be characterized by structured and engaging methods
The Dark Web and the Digital Law, The Ongoing Battle Against Cybercrime
Full text linkThe internet has become the basic need of the current generation. Utmost of the population around the world these days is using the internet regularly. The internet is a vast and intricate web of information, connecting billions of users worldwide. Within this web is a hidden layer known as the Dark Web, a space characterized by its anonymity and opacity. The Dark Web is a realm where the law finds itself at odds with a complex web of cybercriminal activities. The Dark Web, a subset of the Deep Web, is intentionally hidden from conventional search engines
Solvability of Generalized Fractional Hybrid Differential Inclusions in Banach Algebras
Full text linkThis research paper study the solvability of hybrid fractional differential inclusions involving generalized Caputo fractional derivative with boundary conditions under certain conditions. The existence theorems are proved by using hybrid fixed–point approach in Banach algebras of Dhage, which he presented in 2006. An example, lastly, is proposed to check the efficiency of the above-mentioned theorems. The results are novel and provide extensions to some of the findings known in the literature
Classical optimal single-step hybrid block techniques for ODEs: Combined basis functions with dynamic collocation strategy
Full text linkWe introduce a new class of block methods based on a hybrid basis of Hermite probabilists’ polynomials and exponential polynomials. The proposed techniques exploit the complementary strengths of both families, offering enhanced accuracy, stability, and flexibility compared with schemes built on a single polynomial type. The methods employ interpolation and dynamic collocation and are formulated within a second-derivative framework. To strengthen their structure, additional terms are generated through the recurrence relation of Hermite probabilists’ polynomials, whose orthogonality provides further advantages over exponential functions. Since the accuracy of numerical methods depends largely on discretization constants, this hybridization, together with the clustered mesh points, help reduce discretization errors and error constants while maintaining stability. Rigorous theoretical analysis establishes A-stability and convergence of the schemes. Although their algebraic order of convergence is relatively low, numerical experiments demonstrate that the methods achieve improved accuracy and competitive precision factors compared with existing block approaches. These results suggest that hybrid polynomial bases provide a promising pathway for the development of robust and efficient block algorithms in numerical analysis
Information Repackaging Revisited: Finding the Balance between Translation Accuracy and Appeal
Full text linkThere is a global rise in movie adaptations. This has contributed to the movies gaining popularity worldwide due to the socio-cultural and linguistic connections among viewers. The current study analyzes Nollywood (English) movie titles translated into Kiswahili and English movie titles translated into Spanish. Findings from a previous study serve as a springboard for the current study. The previous study analyzed Nollywood movie titles adapted for Kiswahili speakers. It outlined several strategies, including translation ellipses, transference, codeswitching, literal translations, insertion, and paraphrasing. The translation methods illustrate the difficulties translators face when they pursue either equivalence or alternative approaches in their target titles. Similar trends can be observed in English movie titles when translated into Spanish. The current study aims to extend this investigation by analyzing Nollywood movie titles in Kiswahili compared to English movie titles translated into Spanish. It analyzes different translation approaches among these contexts to understand how accurately maintaining original content compares to developing appealing titles for people with diverse backgrounds. The research collects data through questionnaires to contribute to existing views on movie title translation and adaptation. The comparative analysis expands understanding of how information repackaging through movie title translation affects socio-cultural and linguistic communication
Computer-Assisted Consecutive Interpreting and Its Impact on Student Interpreters: An Empirical Study Using iFLYTEK Hearing
Full text linkWith the rapid advancement of artificial intelligence technology, the application of Computer-Assisted Interpretation (CAI) in the field of Consecutive Interpretation (CI) has become increasingly prevalent. Existing research predominantly focuses on the synergistic effects of AI tools and professional interpreters in Simultaneous Interpretation (SI) scenarios, while the efficacy of CAI for student interpreters in CI tasks remains underexplored. This study employs empirical analysis to address two core questions: (1) What impact does CAI have on the interpreting quality of student interpreters in CI? (2) What underlying factors mediate this impact?
Adopting a controlled experimental design, the study recruited 11 third- and fourth-year English majors (all with less than 12 months of interpreting training) as participants. Each participant performed two interpreting tasks of comparable theme, length, and difficulty, with the variable being "use or non-use of CAI tools." Quantitative and qualitative analyses were conducted using iFlytek Hearing for real-time transcription and ERNIE Bot for quality evaluation assistance. Questionnaires and semi-structured interviews were utilized to measure and collect participants’ experiential feedback. Data were analyzed using SPSS software, yielding the following conclusions: Findings suggest that while CAI did not significantly improve overall interpreting quality, it partially supported memory and accuracy. However, cognitive overload and interpreter anxiety limited its effectiveness. These results provide empirical evidence for refining CAI integration in interpreter training. However, this experiment, with no training exposure and a rather small sample size, is more of an exploratory study
Pan De Sal Fortified with Cassava Based Sagip Nutri Powder
Full text linkThis study investigates the nutritive value and consumer acceptability of Pan de Sal fortified with cassava-based Sagip Nutri Powder. Specifically, it explores the nutritional composition of the fortified bread, its acceptability based on sensory attributes, and its market potential through a cost and return analysis. Five treatment formulations of Pan de Sal were developed, incorporating varying amounts of turmeric powder and cassava-based Sagip Nutri Powder. Nutritional analysis showed that the fortified Pan de Sal had higher energy, dietary fiber, and protein content compared to the control. Sensory evaluations were conducted among 100 panelists from diverse age groups, who assessed color, taste, odor, and texture. Results showed that the fortified formulations were highly acceptable, with Treatment 5 (10g turmeric and 40g cassava-based Sagip Nutri Powder) being the most favored in terms of taste and texture. The study also indicated that younger consumers, particularly those in the 11-20 age range, had a higher preference for the product. A cost and return analysis demonstrated the commercial viability of the fortified Pan de Sal. Educational materials on the benefits of fortified bread were also suggested based on the findings
Efficacy of Two Hidden Layers Artificial Neural Network Synapticity for Deep Learning: A Case of Pattern Recognition
Full text linkMost research works in Artificial Neural Network (ANN) are accustomed with the use of single hidden layer (SHL) topology without giving considerations to the problem type, its complexity and desired depth of supervised or unsupervised learning. This could be partly due to the inherent complexities associated with the use of more than one hidden layer which in turn affects solution efficiency. However, the trade-off occasionally is between efficiency and effectiveness of result. When effectiveness is prioritized perhaps for sensitive or mission critical systems, then multiple hidden layers can become advantageous. This research has investigated the ability of an Artificial Neural Network (ANN) with two hidden layer topology to exhibit deep learning behaviour in comparison with a single hidden layer architecture ANN system. A two hidden layer (THL) Neural Network was developed and implemented using Microsoft Visual Studio programming suite and applied to a pattern recognition problem. The gradient descent optimization of the back propagation algorithm in a feed forward scheme was used in the development of the supervised ANN which consisted of thirty inputs at the input layer, two hidden layers with five nodes and a single output layer with one node for a Boolean response. Normalized images mapped into a pattern extraction template using principal component analysis (PCA) of the original images served as pre-processed inputs to the two hidden layer architecture with an initial learning rate of η = 0.1 and maximum tolerable rate of η = 0.4 for fast convergence. Iterations for validation of the feed forward back propagation algorithm using three image patterns showed that over 96% recognition of presented data was recorded. Graphical comparison of the results obtained from separate iterative sessions of the One Hidden Layer (OHL) and (THL) architectures under same input-output dataset revealed more visible traits of attained deep learning by the two hidden layer architecture due to enhanced synapticity of additional nodes
Nonlinear viscoelastic Petrovsky equation with fractional damped: Existence and blow-up
Full text linkIn this article, we study a nonlinear viscoelastic Petrovsky equation with fractional damping. First, we establish the existence of a local weak solution by using semigroup theory. Then, we prove the blow up of the solution under suitable conditions
A Hybrid Framework for Securing 5G-Enabled Healthcare Systems
Full text linkThe rapid adoption of 5G technology in healthcare introduces significant challenges regarding data privacy and security. This paper proposes a hybrid framework integrating blockchain, zero-trust architecture (ZTA), and AI-driven threat detection to address these challenges. Blockchain ensures secure, tamper-proof data storage, while ZTA strengthens access control by continuously verifying users and devices. AI contributes by providing real-time threat detection and dynamic response capabilities, making the system more resilient to evolving cyber risks. A systematic literature review was conducted to analyze existing frameworks and identify gaps in 5G healthcare security. The findings reveal that while individual technologies such as blockchain and ZTA are well-established, their integration into a cohesive framework remains underexplored. The proposed hybrid solution effectively mitigates the risks associated with 5G networks by offering a multi-layered security approach. This research contributes to the field by proposing a scalable, adaptable security model suitable for 5G-enabled healthcare systems. Future research should focus on empirical validation, scalability testing, and exploring lightweight alternatives to blockchain and AI for resource-constrained environments. Additionally, investigating the integration of emerging technologies like quantum computing and 6G networks will further enhance the framework’s security capabilities. This study provides a foundation for developing secure, privacy-preserving systems for healthcare in the 5G era