https://repository.umindanao.edu.ph/handle/123456789/2294 2026-05-20T09:48:19Z 2026-05-20T09:48:19Z Arroyo, Jan Carlo T. Sison, Ariel M. Medina, Ruji P. Delima, Allemar Jhone P. https://repository.umindanao.edu.ph/handle/123456789/2323 2026-05-07T19:00:33Z 2022-01-01T00:00:00Z

A cryptographic test of randomness, entropy, and brute force attack on the modified playfair algorithm with the novel dynamic matrix Arroyo, Jan Carlo T.; Sison, Ariel M.; Medina, Ruji P.; Delima, Allemar Jhone P. One critical concern in designing a cryptographic algorithm is its randomness. The randomness test examines the quality of random numbers generated by cryptographic algorithms. In this paper, the National Institute of Standards and Technology (NIST) Statistical Test Suite for Random and Pseudorandom Number Generators for Cryptographic Applications was instrumental in assessing the security of the modified Playfair algorithm with the novel Multidimensional Element-in-Grid Sequencer (MEGS). Moreover, this study determines the level of security of the MEGS-based Playfair algorithm against brute force attacks. Simulation results revealed that the modified cryptographic algorithm could execute the encryption process with randomly generated ciphertext despite having repetitive letters in the plaintext, as evident in the frequency (monobit) test, frequency within a block test, and runs test with p-values > 0.01. Further, the MEGS-based Playfair algorithm was highly resistant against attacks based on the results of the entropy test and the brute force attack analysis. Since the character keyspace of the modified algorithm is 256, attempts to break the ciphertext would cost a large amount of financial and computational resources. The use of a 16x16 dynamic matrix with matrix rotation, matrix shifting, matrix rolling, and crossover operations enhanced the performance of the Playfair algorithm, improving its resilience to attacks. This article evaluates the security performance of a modified Playfair Cipher algorithm using a novel dynamic matrix by analyzing its randomness, entropy, and resistance against brute force attacks.

2022-01-01T00:00:00Z Leikuma-Rimicane, Liene Baloran, Erick T. Ceballos, Roel F. Medina, Milton Norman D. https://repository.umindanao.edu.ph/handle/123456789/2313 2026-05-07T05:32:47Z 2022-01-01T00:00:00Z

The role of higher education in shaping global talent competitiveness and talent growth Leikuma-Rimicane, Liene; Baloran, Erick T.; Ceballos, Roel F.; Medina, Milton Norman D. The role of higher education in shaping global talent competitiveness and growth in the modern world is an excellent area of interest. To meet the growing demand for talented human capital in today's modern industries, HEIs must mobilize and standardize policies and develop programs for talent management among students as the future workforce. This study aimed to analyze the role of HEI in shaping talent competitiveness and growth. Selected higher education indicators that characterize the talent and growth development of at least 117 countries were analyzed using R version 4.1.3. The Global Talent Competitiveness Index (GTCI) was used to measure the talent competitiveness of the selected countries. To measure talent growth, we used the average annual change in the GTCI over the last five years; hence secondary data on the role of higher education in shaping talent competitiveness and growth were used. Various academic factors and skills that stimulate global talent competitiveness and growth are outlined in this study. Considering the factors that affect talent competitiveness and growth globally, colleges and universities place a strong emphasis on developing graduates' skill sets, advocating for, and organizing aspects in terms of mean years of schooling, including professional development, internet, and digital skills, and getting students ready for international co-invention and scientific publication. An article that examines how higher education institutions contribute to developing globally competitive talent by fostering skills, knowledge, and opportunities for professional growth.

2022-01-01T00:00:00Z Syting, Christian Jay O. Gildore, Phyll Jhann E. https://repository.umindanao.edu.ph/handle/123456789/2309 2026-05-07T05:31:43Z 2022-01-01T00:00:00Z

Teachers’ linguistic politeness in classroom interaction: a pragmatic analysis Syting, Christian Jay O.; Gildore, Phyll Jhann E. This study aimed to uncover the different structures of linguistic politeness used in the utterances of the teachers in classroom interaction. More specifically, the analysis made use of House and Kasper's (1981) Politeness Linguistic Expressions, Brown and Levinson's (1987) Politeness Strategies, and Leech's (1983) Politeness Maxims. Using observation and interview, several structures of linguistic politeness were unearthed. Firstly, the politeness linguistic expressions involved politeness markers, consultative devices, downtoners, committers, forewarning, hesitators, and agent avoider. Secondly, the politeness strategies involved positive politeness, negative politeness, off-record strategy, and bald-on record strategy. Lastly, the politeness maxims involved tact, approbation, modesty, and agreement maxim. Politeness is a non-value-laden linguistic phenomenon where it does not always mean what people in the here-and-now take it to mean, but there can always be a conventional ways of expressing so in a particular social interaction. The structures of linguistic politenesss do not always lead to conflict-avoidance, but they only contribute to the success of the effect of the expressions used. Hence, whatever may seem to have been considered as conventionally conventionalized or non-conventionalized politeness in a context, several factors must need to be considered for an expression to be a form of politeness strategy that performs supportive facework. An article that explores how teachers use linguistic politeness strategies in classroom interactions, analyzing their communication through a pragmatic perspective.

2022-01-01T00:00:00Z Pahuriray, Archolito V. Basanta, Joe D. Arroyo, Jan Carlo T. Delima, Allemar Jhone P. https://repository.umindanao.edu.ph/handle/123456789/2304 2026-05-07T05:30:41Z 2022-01-01T00:00:00Z

Flexible learning experience analyzer (FLExA): sentiment analysis of college students through machine learning algorithms with comparative analysis using WEKA Pahuriray, Archolito V.; Basanta, Joe D.; Arroyo, Jan Carlo T.; Delima, Allemar Jhone P. The spread of the COVID-19 pandemic broughtsignificant changes in society. Emerging technologies like artificial intelligence and machine learning devices improved several industries, especially in academe and higher education institutions. In this study, a model to analyze and predict college students' sentiments from the Flexible Learning Experience portal was built using several supervised machine-learning techniques. Waikato Environment for Knowledge Analysis (WEKA) application was used to apply the Naive Bayes (NB), C4.5, Random Forest (RF), Support Vector Machine (SVM), and K-Nearest Neighbors (KNN) algorithms. Additionally, a comparative analysis of different machine-learning methods was applied. The experimental results revealed that the C4.5 algorithmobtained the highest accuracy than other algorithms. The effectiveness of each algorithm was evaluated and compared using 10-fold cross-validation (CV), taking into account the major accuracy metrics, instances that were accurately or inaccurately classified, kappa statistics, mean absolute error, and modeling time. Moreover, results show that the C4.5 algorithm outperformed other algorithms by classifying the model with 98.13% accuracy, 0.0132 mean absolute error, and 0.00 seconds of training time. Furthermore, teachers and college administrations were well accustomed to the sentiments and problems of college students and might act as a decision-support mechanism mainly as they deal with the new setting during this time of crisis. An article that examines college students’ perceptions of flexible learning by performing sentiment analysis with multiple machine learning algorithms and comparing their performance using WEKA.

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