: Due to its solid mathematical foundations, Formal Concept Analysis (FCA) has become an emergent topic in the area of data analysis and knowledge discovering. Information is represented in a binary table defining a relation between a set of objects and a set of attributes—the formal context. The knowledge extracted from the formal context allows to identify useful patterns in data in different forms. One very useful knowledge representation in FCA are implications among attributes which are validated over the objects. The most outstanding feature of implications is that they can be managed by means of inference systems. Equivalent sets of implications can be obtained using different logic-based transformations. The aim of these transformations is to turn the original set of implications into an equivalent one fulfilling some desired properties. Among them, the directness and optimality are very popular targets because getting a direct-optimal basis ensures that the closure of a set of attributes may be computed with lower cost (time and resources). In this work, we introduce a new method to compute the direct-optimal basis which improves the existing ones. The new method reduces the input in a first stage and is guided by the idea of limiting the growth of the intermediate sets of implications as a way to improve the performance. We illustrate the good features of the new method with both a detailed example and by experimental evaluation.

Elena Maria Giordano, Kristof Driesen, Paolo De Luca, Maria Luisa Fasolato, Alessia Conti,. "From Implicational Systems to Direct-Optimal Bases: A Logic-Based Paradigm Shift." Computer Engineering, vol. 13, no. 4, pp. 1–13, 2024.

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: Academic success in further mathematics is perceived to have a significant contribution towards the development of science and technology in any nation. The main objective of this study is to identify the major determinants of students’ academic success at WASSCE further mathematics. Two public schools in Hemang Lower Denkyira District constituted the study area with a sample of 84 students. Data for 2016/1017 WASSCE academic year group tracked from the documented records of the two selected schools in the District with 1:1 gender ratio were used for the study. Explanatory factors were; Mock examination, Age, Student Residence, School Location, and Gender on the target variable WASSCE grade. A three- stage stratified cluster sampling technique was used to select the two schools as well as classes and subject area under study. IBM SPSS Version 21 was used to analyse the data for the purpose to modelling multiple logistic regression with a binary response ‘WASSCE grade’ (upper grade/lower grade) against the systematic component of linear combination of predictor variables at 95% Confidence Interval. The study adopted the ex-post-facto research design. The model correctly classifies 77.4% of the overall cases indicating its prediction accuracy (robustness) and the extent to which it accurately predicted students’ WASSCE grades. AUROC = 0.823, and Hosmer and Lemeshow test had p=0.540 > 0.05 indicating goodness-of-fit of the model. Three (mock examination, school location, and gender) out of five predictors made significant contribution to model with no multicolinearity among the predictors. These variables are the major determinants predicting students’ WASSCE grade/performance in further mathematics. The study concluded that mock examination is reliable and thus should be centralized and supervised by the area education officer to make it more stringent, and there should be equity in resource allocation where both the less and well-endowed schools are equally supplied with teaching-learning resources, and finally, the education in its contents, designing and application should be gender solicitous. Computer Engineering ISSN: 10003428 Volume 13 | Issue 4 | Year 2024 https://journalofcomputerengineering.com/ © 2024 Computer Engineering. All Rights Reserved. Page 14

Adjepong, Kweku Baffour (PhD), Owusu-. "2016/1017 WASSCE academic year Exploring Predictive Models group tracked from the documented records of the two selected schools in for Student Success: A the District with 1:1 gender ratio Multivariate Analysis of were used for the study. Explanatory Further Mathematics factors were; Mock examination, Age, Student Residence, School Performance." Computer Engineering, vol. 13, no. 4, pp. 14–36, 2024.

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: Large-area nanostructured transducer for absorption opto-plasmonic measurements in the ultraviolet visible UV-VIS spectral range have been realized by colloidal lithography. The design and simulation performed guarantee the optical behaviour of the nanostructured transducers. Morphological characterization by AFM microscopy evidences the nanodome structure of the object realized in array configuration. A microfluidic device was optimized to perform measurements in real time. Qualitative evaluation of the peroxides’ and bisphenols’ concentration in extra virgin olive oil (EVOO) have been obtained by following the variation in the plasmonic resonance monitoring of a suitable array nanodome structure deposited onto a glass substrate. Comparison of the obtained results with laboratory-standard methodologies gives us guaranteed support of the potential of the realized technology.

Alessandro De Santis, Francesca Maria Caruso, Lorenzo Pinto, and Giulia Maria. "Plasmonic Nanodome Transducers for the Detection of Peroxides and Bisphenols in Extra Virgin Olive Oil." Computer Engineering, vol. 13, no. 4, pp. 37–46, 2024.

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Analytic tools are useful for detecting patterns in education data and providing insights about student performance and learning. This study compared six supervised learning algorithms (e.g., linear regression, ridge regression, lasso, regression trees, random forests regression, gradient boosted regression) and identified features important for predicting student performance. The dataset consisted of N=1044 observations from two secondary schools in Portugal [1]. Performance was assessed by final grades (range: 0-20) in two courses, mathematics and Portugese. The models were fit to training data with 27 independent variables and evaluated on a testing subset. Overall, performance was lower for students in mathematics than Portugese. The models selected a similar set of variables as important for predicting performance: Mother’s education level, student plans for higher education, and weekly study time were positively related to predicted performance, whereas course subject, school educational support, and romantic relationships were associated with decreased student performance. The models differed in the number, weighting, order and importance given to the predictor variables. Linear regression provided a model with 13 predictors. Ridge regression shrank the coefficient estimates toward zero; the lasso performed variables selection for a model with 20 predictors. There was a tradeoff between model complexity and interpretability. The single pruned regression tree provided a simple, interpretable non-linear model that branched on four features. Random forests regression and gradient boosting reduced overfitting, but were more difficult to interpret. Advantages and limitations of the different models are considered. Applications for educational data mining (EDM) and learning analytics (LA) are discussed. 1 KEYWORDS Predictive Modeling, Variable Importance, Learning Analytics

Ethan J. Blackwood and Ava L. Thompson. "Enhancing Student Success through Predictive Modeling in Data-Driven Learning Analytics." Computer Engineering, vol. 13, no. 4, pp. 47–57, 2024.

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Various definitions, forms, and theories related to Corporate Social Responsibilities (CSR) are presented in this article. Nowadays most corporations follow different methodologies to implement CSR approach. But in most cases corporation follow CSR methodology that reflects only its shareholders’ interest neglecting its community interest. Critical analysis and comparison for the main CSR theories are presented also, followed by a conclusion about a comprehensive form of CSR that targets both shareholders and community interest. Three of the main CSR theories and models have been represented and analyzed in this article: The Carroll Theory, The Triple Bottom Line Theory, and The Stakeholder Theories. Since any business corporation has to adopt one of these theories, this study reveals the strength and challenges of every theory. There is no doubt that every theory has been well analyzed by its founder or scholar, but an advanced understand for every theory will make it possible for a corporation’s managers and decision makers to implement long term social and environmental strategies with more accurate achievements. This article is divided into four main sections, the first section presents Carroll’s model for CSR, followed by the second which is about the Triple Bottom Line theory for CSR, and the third represents the Stakeholder theory. The fourth section analyzes three CSR theories and sheds light on the core responsibility of every theory. Comprehensive analysis for the three recognized CSR models were represented in a table to help readers to locate and clarify systemic differences and common features between the three theories. The last section of the article reveals three main outcomes, the first outcome represents a recommendation for the implementation process of adopting any of the three theories, and which is divided into an internal and external level. The second outcome reveals the importance of addressing a specialized committee for CSR by a company, followed by the third outcome that discusses some of the implications of this analysis for future CSR research and studies.

Anastasija Pavlenko and Julian S. Everett. "Reevaluating Corporate Social Responsibility: A Theoretical and Modeling Framework." Computer Engineering, vol. 13, no. 4, pp. 58–66, 2024.

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We examined 638 Lepidoptera specimens on the territories of 13 European countries in our search for parasitoids. We collected eggs, larvae and pupae. In total, 251 Lepidoptera species were identified, belonging to 169 genera from 30 families. Of the total sample, approximately one-third (32.23%) were parasitized. In 168 samples (26.42%), we identified only one parasitoid species per host. In addition to these data, 224 plant species from 114 genera were identified, of which the vast majority were feeding plants.

Dr. Frank Kargl. "Ecological Patterns of European Lepidoptera: A Multifaceted Analysis of Non-Adult Stages and Parasitoid Communities." Computer Engineering, vol. 13, no. 4, pp. 67–72, 2024.

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: In this work, we prove a common fixed point theorem of type Jungck under a generalized definition of weak commutativity and a well-known contractive inequality by commingling both conditions in the proof. Some open questions are also indicated and intimately connected (or not?) to the metric to be used.

Alessandro Bianchi, Sofia Rodriguez, and Lorenzo Ferrari. "A Convergence Theorem via Type Jungck and Weak Commutativity Conditions." Computer Engineering, vol. 13, no. 4, pp. 73–81, 2024.

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: Attention to cultural diversity is a necessity at online higher education in management (2004) postulated a framework for conceptualizing dimensions of intercultural competence in its development model of intercultural sensitivity. Complementary, Intercultural Learning Model (Beamer, 2016) emphasizes the importance that students are able to encode and decode the differences in messages emitted by people of different cultures. In addition, higher education institutions should attend perceived cultural distance emerges as an outstanding concept related to the management of interculturality by the management of institutions. The aim of this research is develop a systematic indexed literature review at the field of intercultural approach to the online teaching and learning at management. Systematic literature review described by Fink (2005) is the methodology used. It consist on identifying, evaluating, synthesizing, interpreting and analyzing research literature. This review is based on Business Source Complete (EBSCO) that offers papers from 1936 to 2016 with 1,232 documents; Web of Science, from 1995 to 2016 with 207 documents and Scielo, from 1999 to 2016 with 358 documents. The content analysis applied shows that 74% of the papers' fragments can be categorizes as integration. Therefore, the papers articles avoid the importance of achieving integration at the online teaching-learning processes in management.

Sofia Rodriguez-Mendoza, Julian Sánchez-González. "An Interdisciplinary Examination of Intercultural Pedagogies in Online Learning Environments." Computer Engineering, vol. 13, no. 4, pp. 82–88, 2024.

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The objectives of this study were to determine the effect of cadmium (Cd) on glucose metabolism disruption in liver cells homogenate in vitro. The glucose metabolism disruption was analyzed by measuring the level of liver glucose, glycogen and methylglyoxal (MG), and the activity of glucokinase activity. In this experiment, a liver sample was taken from male rats (Rattus novergicus). Samples then homogenized and divided into four groups with; C served as control which contains liver homogenate only; T1 which contains liver homogenate + 0.03 mg/l of cadmium sulphate (CdSO4); T2 which contains liver homogenate + 0.3 mg/l of CdSO4; and T3 which contains liver homogenate + 3 mg/l of CdSO4. After treatment, liver glucose, glycogen, and MG levels, and glucokinase activity were estimated. The activity of liver glucokinase was estimated by measuring the Michaelis-Menten constant (Km) value. The results revealed that Cd exposure could significantly increase glucose and MG levels, the Km value of glucokinase, and decreased the glycogen level in liver cells (P<0.05). These results indicated that Cd exposure induced the disruption of glucose metabolism in the liver.

Maria Sofia Rodriguez, Rania Ahmed Ali, Ahmed Hassan Elsayed, Fatima Zohra Benkirane,. "The Diabetogenic Impact of Cadmium on Liver Tissue In Vitro." Computer Engineering, vol. 13, no. 4, pp. 89–94, 2024.

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