Online education has become the norm for higher education institutions (HEIs) during this COVID-19 pandemics. HEIs are required to implement a fully online learning system that is structured and readily accessible with the assistance of a learning management system (LMS), including in developing countries such as the Philippines. This study aims to assess factors that positively influence the perceived satisfaction of engineering students when using the LMS during the COVID-19 pandemic in the Philippines. Additionally, it aims to integrate two models: Task Technology Fit (TTF) and Technology Acceptance Model (TAM), with added variables such as the content of the learning management system, social presence, and social space. Upon deploying the convenience sampling, a total of 1011 engineering students responded in the online survey, which consisted of 81 questions. Structural equation modeling (SEM) showed that the Task Technology Fit was positively influenced by technology, individual, and task characteristics. Moreover, behavioral intention to use LMS was positively influenced by perceived usefulness and perceived ease of use. Furthermore, Task Technology Fit had a significant direct effect on behavioral intention to use LMS, which subsequently led to perceived satisfaction. This study is among the first to explore factors affecting perceived satisfaction among engineering students in using the LMS in the Philippines during the COVID-19 pandemic. To evaluate the perceived satisfaction of students in using the learning management system, future works can be extended and the model can be applied in other countries.

With the increasing adoption of solar PV generation system, it is essential to analyze the impacts to the distribution system especially if PV units is installed in both MV and LV network. This paper develops a methodology that determines the solar PV hosting capacity of a distribution network considering the effect between the interactions of MV and LV network at different voltage levels. A comprehensive approach was used including complete LV network modeling characteristics. The interaction between the MV and LV network offers an advantage to other approaches described in the literature. A modified 25-bus test system with complete MV and LV network model was tested and an integrated MV-LV power flow solution was used to analyze the impacts on its interactions. Peak and off-peak load conditions of different customer types were also considered. Aggregate installation was examined and it was shown that single solar PV installation is sufficient for the hosting capacity quantification. Also, LV network hosting capacity installations have minimal effect on the MV network. Results show that the main limitation of MV hosting capacity is the LV network voltage problems.

The Philippine stock market, just like most of its neighbors in the region, was seriously impacted by the global pandemic COVID-19. Investors remain hopeful while continuing to seek great ones in the damaged market. This paper developed a methodology for portfolio selection and optimization with the use of technical analysis, machine learning techniques, and portfolio optimization model. The combined methods of technical analysis, K-means clustering algorithm, and mean-variance portfolio optimization model will result in the development of the proposed TAKMV method. The study aims to integrate these three important analyses to identify portfolio investments. This paper uses the average annual risk and annual rate of return data for the years 2018 and 2020 to form the clusters and assessed the stocks that correspond to the investor's technical strategy such as Moving Average Convergence/Divergence (MACD) and Hybrid MACD with Arnaud Legoux Moving Average (ALMA). This paper solved the risk minimization problem on selected shares of the companies, based on the mean-variance portfolio optimization model. There are 230 and 239 companies for 2018 and 2020, respectively, listed in Philippine Stock Market, and all simulations were performed in MATLAB environment platform. Results showed that MACD strategy dominates the MACD-ALMA strategy in terms of the number of assets with a positive annual rate of return. The MACD works efficiently in the pre-COVID-19 condition while MACD-ALMA works efficiently during-COVID-19 condition, regardless of the number of assets with a positive annual rate of return. The results also show that the maximum expected portfolio return (R_P) can be achieved using the MACD and MACD-ALMA in the pre-and during-COVID-19 conditions, respectively. The MACD-ALMA shows an advantage during high-risk market conditions and can also provide maximum R_P. The performance of the TAKMV method was validated by applying its results and comparing it to the next year's historical price. The 2018 results were compared to 2019 data and the 2020 results were compared to 2021 data. For consistency, the comparison was applied to the same company per portfolio. Simulation results show that the MACD strategy is more effective compared to MACD-ALMA.

One of the key issues nowadays in using Holt-Winters Method of forecasting is the appropriate selection of smoothing coefficients. To identify values of smoothing coefficients, an optimization approach is explored that minimizes a forecasting error like Mean Squared Errors (MSE) or Mean Absolute Deviation (MAD). This paper develops a methodology that optimizes forecasting error by determining the optimal smoothing coefficients of the Holt-Winters Method using Genetic Algorithm (GA). This paper focuses on the Mean Square Error (MSE) as an objective value of the optimization problem. The efficiency of the proposed approach was verified using actual test cases based on rice stock commodity in the Philippines. Different variants of the Holt-Winters Method were examined and the result shows that additive seasonal effect was more appropriate for the rice stock data. The proposed approach was compared to other models and the results are promising.

Process Improvement is an aspect of organizational development in which a series of actions are taken by a process owner or process analyst to identify, analyze and improve existing business processes within an organization for optimization and to meet new quotas or standards of quality. The shoe industry in Marikina City which is the shoe capital of the Philippines is lagging behind its neighboring countries in East and Southeast Asia in terms of shoe production. This paper aims to increase the productivity of a shoe manufacturing company by utilizing the machines in the production area, improving the process layout, and ensuring quality is present in every element of the shoe making process. Analysis tools are utilized to analyze the existing business process such as Ishikawa diagram, time and motion study, flow process chart, ISO flow process, statistical computation, process layout, and cost benefit analysis. The results show that the proposed layout machine will have an increase in production output by 13.11%. This paper recommends the following; (1) the improvement of time (12.54% faster) and distance (208.80% shorter) of each process giving way to a new layout. (2) Introduction of new machines that will speed up the production while maintaining the quality.

The present development in distribution utilities is to adopt Advanced Distribution Management System (ADMS) for distribution automation. The distribution power flow solution to be used is one of the key successes of this initiative. This paper develops a new algorithm in solving power flow solution from medium voltage (MV) up to the low voltage (LV) level or from the distribution substation up to the customer side. A modified backward/forward sweep power flow algorithm was proposed. The method combines MV and LV power flow in a single power flow algorithm and provides an efficient tool for distribution power flow analysis. Three-phase unbalanced distribution characteristics model in the MV and comprehensive secondary network modeling to account different loading and customers characteristics in the LV were used. A computer program has been developed using Matlab platform and the robustness of the proposed algorithm is verified using a developed 25-bus distribution network and the result is compared with Radial Distribution Analysis Package (RDAP).