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With the increase of the complexity of practical problems, the optimization of sparse linear equations becomes more and more important. Based on two kinds of solutions of linear equations: direct solution and iterative solution, this paper probes into the solutions of sparse matrix equations. For the direct solution, the Gauss elimination method without selecting pivot elements, column selecting pivot elements, and all selecting pivot elements is selected to explore the performance of sparse matrix solution for triplet storage. For the iterative method, we select the GMRES method and explore three methods including general GMRES, GMRES with LU pretreatment, and GMRES with LU pretreatment and restart. Finally, we compare and analyze the performance differences of all the above direct and iterative solutions, and find that the GMRES method restarted after incomplete LU decomposition can be used as a better general solution of general linear sparse matrix equations. At the same time, the applicable matrices of various methods and their shortcomings are given.

A herpetological survey was undertaken in the Cleopatra’s Needle Mountain Range in Palawan, Philippines, on December 3-12, 2015 organized by the Center for Sustainability – a non-government, non-profit environmental organization in Palawan. The survey aimed to gather initial data on wildlife, including reptiles and amphibian populations from this biogeographically distinct region as supplementary requirements for its declaration as an officially protected area. The survey led to the rediscovery of Malatgan River Caecilian (Ichthyophis Weberi Taylor, 1920) in Palawan, Philippines – an elusive caecilian that has not been observed since 1961. We described here several aspects of the biogeography of the species in Palawan biogeographic region, Philippines.

The study was conceptualized to assess the effect of somatic cell count on the quality of raw milk and soft-white cheese. Cow’s milk was classified into normal (T1), trace (T2) and positive 1 (T3) based on the direct microscopic somatic cell count (SCC). Soft-white cheese was subjected to quality changes; such as physio-chemical compositions: pH, titratable acidity, moisture content, total solids, protein and fat recovery; and total microbial count. Milk samples were subjected to quality analyses prior to cheese manufacture. All samples passed the alcohol precipitation and clot-on-boiling tests. Significant differences were observed in the pH, titratable acidity, moisture, protein, fat and total solids contents of cheese made from T1, T2 and T3 milk. Cheese from normal milk had the lowest titratable acidity from day 0 until day 11 indicating its good keeping quality. The high number of microbial counts even on the 0 days of storage has been observed in soft-white cheese made from the high number of somatic cells. The findings of the study indicate that milk with elevated SCC could compromise the typical sensory quality of the product and could pass the standard quality assessment; however, the quality of the resulting product would be inferior to normal milk. It is recommended that SCC determination be included in the quality assessment protocol on the farm.

Automatic Student performance prediction is a crucial job due to the large volume of data in educational databases. This job is being addressed by educational data mining (EDM). EDM develop methods for discovering data that is derived from educational environment. These methods are used for understanding student and their learning environment. The educational institutions are often curious that how many students will be pass/fail for necessary arrangements. In previous studies, it has been observed that many researchers have intension on the selection of appropriate algorithm for just classification and ignores the solutions of the problems which comes during data mining phases such as data high dimensionality, class imbalance and classification error etc. Such types of problems reduced the accuracy of the model. Several well-known classification algorithms are applied in this domain existing models a student performance prediction model based on supervised learning decision tree classifier. In addition, an ensemble method is applied to improve the performance of the classifier. Ensemble methods approach is designed to solve classification, prediction problem. we propose a method for predicting final grades of students by a Recurrent Neural Network (RNN) from the log data stored in the educational systems. We applied this method to the log data from 108 students and examined the accuracy of prediction. From the experimental results, comparing with multiple regression analysis, it is confirmed that an RNN is effective to early prediction of final and suitable job for the student based on their academic performance and knowledge on skill set.

This study aims to examine whether there is an effect of awarding, providing transport fee for submitting/collecting SPPT and giving raffle prizes to the productivity of PBB-P2 tax collectors in Bondowoso Regency. The population in this study is the tax collectors of PBB-P2 in Bondowoso Regency. Given the large number of populations in this study, sampling using the Slovin formula can be obtained as many as 291 respondents. The data analysis method used multiple regression analysis with latent variables using SPSS 22.0 software. Based on the results of data analysis, it shows that the transport fee awarding for delivery/billing of SPPT and the giving of raffle prizes partially and simultaneously affect the productivity of PBB-P2 Tax collectors in Bondowoso Regency.

Over the years, economists have debated the reasons for differences among countries’ economic growth and development. This study examines the impact of institutional quality and fiscal policy on economic growth and development in Nigeria using time series data spanning from 1970-2016. The study employed Augmented dickey fuller (ADF), Philip person(PP) and Kwiatkowski-Phillips-schmids-shin(KPSS) for unit root test, some of the variables I (0)and some are I (1), which called for cointegration test using  Johansen cointegration test. The result shows three cointegrated equations, and ARDL was used to estimate the short and long-run impact of institutional quality and fiscal policy on economic growth. The result indicates that institutional quality, government expenditure, and the lag of GDP positively impact economic growth and development in Nigeria in both the short and long run. At the same time, fiscal deficit and inflation positively impact economic growth in the long run but are not statistically significant. Similarly, fiscal policy harms economic growth in Nigeria in the short run but has a positive impact in the long run. The study identifies the importance of institutional quality as a determinant of economic growth and development. The implication is that if the roles of institutions are secure, it will help secure property rights, which will provide incentives for economic growth in the world. It will also lead to an efficient allocation of government expenditure and fiscal policy, which will bust economic growth and development.

The study examined the effects of real exchange rate fluctuations on the economic growth of Nigeria from the periods 1986-2018. The study employed Johansen Co-integration, Vector Error Correction Mechanism and Autoregressive Conditional Heteroskedasticity (ARCH). From the results, the study shows that fluctuation in exchange rate negatively influences the growth of the economy, export volume indicates a positive relationship both in the short and long-run on the growth of the Nigerian economy, import indicates negative relationship while the inflation rate is positive and insignificant on the growth of Nigeria economy. The autoregressive Conditional Heteroskedasticity (ARCH) test indicates that real exchange rate fluctuation is persistent in Nigeria. In line with these findings, the study recommended that government should strengthen the exchange rate management framework in the country and take into consideration international fluctuations in the market. For this to be effective, requires the joint efforts of the monetary policies to awake to their core functions.

The COVID-19 crisis has forced education systems worldwide to find alternatives to face-to-face instruction. As a result, modular distance learning has been used by teachers and learners with special educational needs on an unprecedented scale. Teachers of Bagong Nayon II National High School who are handling learners with special educational needs served as writers and evaluators in the Innovative Learning Resource Material entitled “Enhanced Learning Activity Sheets for Learners with Special Educational Needs” (E-LAS for LSENs) that will be used by the LSENs itself through the guidance and support of their parents, teachers, and the school in general. This project aims to supply learning resources for the LSENs’ continuous learning for instruction across all disciplines focusing on the needs of the special education students during the COVID-19 pandemic. Therefore, this study sought to examine the perception of parents of learners with special educational needs on the enhanced learning activity sheets developed by the teachers. The research was carried out in Bagong Nayon II National High School. The study used a survey research design. A total of 25 respondents participated in the study and the instrument used for data collection was the online survey questionnaire. Quantitative data were analyzed by Excel to generate figures. According to the findings, it was confirmed that the majority of the parents of LSENs find that the enhanced learning activity sheets were appropriate learning materials that would be a great help for the parents and learners with special needs to successfully access the needed materials in the new normal learning. In addition, this learning resource material was corroborated as an effective approach based on the perception of the parents of LSENs to fill in the gap in the absence or lack of modules for the Learners with Special Educational Needs. The researcher believes that this can contribute to the attainment of excellence and quality of education in the Special Education Program in the school and the Schools Division of Antipolo.

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