Businesses play an important role in the economy in most countries. Businesses contribute to increased productivity, output and jobs for the economy. Therefore, governments of countries always create favorable business environments to help businesses operate more efficiently, and thereby contribute to the economy. Transforming the industrial revolution 4.0 has brought businesses certain benefits to operations, improving productivity and efficiency. Using data in real estate businesses, through regression analysis, the research results confirm the technology factor has not yet affected the financial performance of enterprises, which can show that businesses need enough time to absorb technology in production activities to have a change in its output. In addition, there exists the negative relationship of leverage in the business and financial performance. Or it can also be confirmed that enterprises that choose their own capital are often more effective than enterprises that choose capital from loans and external financing. The study also confirms that enterprises with the ability to manage total asset turnover have higher financial efficiency. However, the research shows that interest rates have a negative effect on business operations, businesses with high interest rates have a negative effect on business operations, and vice versa.

This paper aimed to examine the determinants affecting students’ Grade Point Average (GPA) at the colleges of science in Prince Sattam Bin Abdul-Aziz University (PSAU). The study applied two approaches of Ordinary Least Square Method (OLS) and Quantile Regression (QR) to investigate the relationship between GPA and different factors; including secondary school rate, achievement test, gender, and department. The data were collected from the Deanship of Admissions and Registration for the academic year (2018) at PSAU. The sample size included (175) students selected from four departments. The data were analyzed using SAS and SPSS programs. The important results are: secondary school rate, achievement test, and gender were revealed to be variables that significantly impact GPA at all quantile levels. At 0.95 quantile the variable department has a significant effect on GPA. The OLS method revealed the significant effect of all four variables secondary school rate, achievement test, department, and gender on GPA. The study recommended that policy makers in higher education should think to add a new criterion for admission according to the privacy of every college or university.

The study investigates determinants important factors influencing apartment prices in Ho Chi Minh city, the biggest economic center of Vietnam. More especially, the study is conducted by collecting survey data of 124 apartments successfully traded during the first six months of 2019. Regression analysis results indicate that apartment prices were positively influenced by size of apartment, presence of balcony, presence of swimming pool, presence of shopping malls and periodic rental income or value. Moreover, proximity to the city center exerts a negative impact on apartment prices. The findings provide some empirical evidence employing survey data on apartment prices in Vietnam. The results are essential for not only Ho Chi Minh city but also other provinces in Vietnam.

The present study investigates performance and feasibility of application of low cost cemented carbide insert in dry machining of AISI 52100 steel hardened to (55 ± 1 HRC) which is rarely researched as far as machining of bearing steel is concerned. Machinability studies i.e. flank wear, surface roughness and morphology analysis of chip has been investigated and statistical regression modeling has been developed. The test has been conducted based on Taguchi L16 OA taking machining parameters like cutting speed, feed and depth of cut. It is observed that uncoated cemented carbide insert performs well at some selected runs (Run 1, 5 and 9) which show its feasibility for hard turning applications. The developed serrated saw tooth chip of burnt blue colour adversely affects the surface quality. Adequacy of the developed statistical regression model has been checked using ANOVA analysis (depending on F value, P value and R2 value) and normal probability plot at 95% confidence level. The results of optimal parametric combinations may be adopted while turning hardened AISI 52100 steel under dry environment with uncoated cemented carbide insert.

Application of Artificial Neural Network (ANN) in modeling of combined cycle power plant (CCPP) with dry cooling tower (Heller tower) has been investigated in this paper. Prediction of power plant output (megawatt) under different working conditions was made using multi-layer feed-forward ANN and training was performed with operational data using back-propagation. Two ANN network was constructed for the steam turbine (ST) and the main cooling system(MCS). Results indicate that the ANN model is effective in predicting the power plant output with good accuracy.

The article examines the impacts of cash holding ratio on the performance of firms listed in Vietnam for the period of 2008-2018. The author finds that the proportion of cash holding had a positive impact on the firm performance. The study also shows the impacts of financial leverage, the ratio of tangible assets, firm size, and sales growth on the firm performance. In addition, this is the first study in Vietnam to find a positive and statistically significant impact of state ownership on the firm performance. Thus, the firm performance can be achieved by the effective state capital management. The results of this study provide a reliable basis for financial managers to make appropriate cash holding decisions to improve the firm performance.

Electronic commerce is a way of sale that has come to stay. It helps companies to overcome physical barriers, and in theory, it increases their sales. However, does electronic commerce have any impact on the firms' revenue? This research sought the answer by employing OLS and quantile regressions in a sample of 2164 Peruvian retail firms. The dataset was obtained through the INEI economic survey of 2019, which was the last one. For methodological purposes, electronic commerce was compared against the other sales channels employed by the studied firms. It was found that electronic commerce positively impacted the income in firms with more enormous revenues but was still low compared with traditional commerce forms.

The aim of this study is to correlate work piece material hardness with surface roughness in prediction studies. The proposed model is for prediction of surface roughness of tool steel materials of hardness 55 HRC to 62 HRC (±2 HRC). The machining experiments are performed under various cutting conditions using work piece of different hardness. The surface roughness of these specimens is measured. The result showed that the influence of work piece material hardness on surface finish is significant for cutting speed and feed in CNC end milling operation. It is also observed that the surface roughness prediction accuracy of Adaptive neuro fuzzy inference system using triangular membership function is better than Gaussian, bell shape membership function and regression analysis. Surface roughness prediction accuracy with material hardness as input parameter is 97.61%.

The objective of the study is to assess the performance of multilayer coated carbide insert in the machining of hardened AISI D2 steel (53 HRC) using Taguchi design of experiment. The experiment was designed based on Taguchi L27 orthogonal array to predict surface roughness. The S/N ratio and optimum parametric condition are analysed. The analysis of variance has also been carried out to predict the significant factors affecting surface roughness. Based on Taguchi S/N ratio and ANOVA, feed is the most influencing parameter for surface roughness followed by cutting speed whereas depth of cut has least significant from the experiments. In regression model, the value of R2 being 0.98 indicates that 98 % of the total variations are explained by the model. It indicates that the developed model can be effectively used to predict the surface roughness on the machining of D2 steel with 95% confidence intervals.

Turning hardened component with PCBN and ceramic inserts have been extensively used recently and replaces traditional grinding operation. The use of inexpensive multilayer coated carbide insert in hard turning is lacking and hence there is a need to investigate the potential and applicability of such tools in turning hardened steels. An attempt has been made in this paper to have a study on turning hardened AISI 4340 steel (47 ± 1 HRC) using coated carbide inserts (TiN/TiCN/Al2O3/ZrCN) under dry environment. The aim is to assess the tool life of inserts and evolution of flank wear with successive machining time. From experimental investigations, the gradual growth of flank wear for multilayer coated insert indicates steady machining without any premature tool failure by chipping or fracturing. Abrasion is found to be the dominant wear mechanisms in hard turning. Tool life of multilayer coated carbide inserts has been found to be 31 minute and machining cost per part is Rs.3.64 only under parametric conditions chosen i.e. v = 90 m/min, f = 0.05 mm/rev and d = 0.5 mm. The mathematical model shows high determination coefficient, R2 (99%) and fits the actual data well. The predicted flank wear has been found to lie very close to the experimental value at 95% confidence level. This shows the potential and effectiveness of multilayer coated carbide insert used in hard turning applications.