The continuous increase in energy consumption has brought worldwide attention to its significant environmental effect, which is triggered by the increase in greenhouse gas emissions, global warming, and rapid climate change. As such, more energy efficient buildings are required to minimize the energy consumption of heating and cooling. The present study introduces a set of machine learning-based models to predict the heating and cooling loads in buildings. This includes back-propagation artificial neural network, generalized regression neural network, radial basis neural network, radial kernel support vector machines and ANOVA kernel support vector machines. The comparisons were conducted as per mean absolute percentage error (MAPE), mean absolute error (MAE) and root-mean squared error (RMSE). Finally, the significance of the capacities of the machine learning models are evaluated using two-tailed student’s t-tests. Results demonstrate that the radial basis function network outperformed the aforementioned machine learning models.

A non-dominated sorting genetic algorithm (NSGA-II) is applied to obtain Pareto optimal solutions in widely used advanced machining processes, i.e., electric discharge machining, electrochemical micromachining, ultrasonic machining, abrasive water jet machining. The solutions obtained using the proposed method is in the form of the Pareto-optimal front, thus, any solution is acceptable and can be utilized to obtain optimum performance of the considered processes. The obtained results using NSGA-II show good agreement with the results of previous researchers. Implementation of the proposed method shows benefits to the process engineer of the industries as they can select alternative parameters based on the requirement.

Village tourism is one of the alternative forms of sustainable tourism that began to be developed in Bali. Bongkasa Pertiwi tourism village is one of the villages designated as a tourist village with a variety of natural potential. The purpose of this research is to analyze the strategy and development program of the Bongkasa Pertiwi Tourism Village, and to analyze the factors that play a role in the sustainability of the Bongkasa Pertiwi Tourism Village. The main data collection technique in this study is through FGD, the results of which are input to the SWOT and MICMAC analysis. The results of the SWOT analysis show that Bongkasa Pertiwi Tourism Village has strong category competitiveness, and high category attractiveness as a tourist village, so the strategic position of the development of the Kenderan tourism village is in the condition of growth and build. The three main factors in the sustainability of a tourist village are the uniqueness of the tourist village, the competence of human resources, and the presence of a driving force that has a link with stakeholders.

The paper studies the monetary approach to exchange rate for a group of five Pacific Basin economies, using quarterly data for the period of post – Asian financial crisis. Estimated results reveal that for Thailand and the Indonesia which were most affected by Asian financial crisis, monetary model did not work for explaining exchange rate movements. For Korea and Malaysia, the results show that there were long-run relationships between exchange rates and their monetary variables. However, the proportionality hypothesis of exchange rate to relative money supply did not hold for the two countries. Conversely, for Vietnam, it appears that the monetary model worked well in explaining exchange rate movements. Especially, the estimated coefficients of money and output variables are consistent with any traditional variants of monetary model.

Caring for cancer patients may create several negative emotions for their family members. Therefore, reducing or alleviating negative feelings are essential in improving mental and physical health of cancer patients’ family members. This research aims to identify the priority levels of the strategies used by cancer patients’ family members to cope with negative emotions, utilizing Analytic Hierarchy. Next, the proposed model is applied in the cases of Vietnamese cancer patients’ family members. Four groups of coping strategies against negative emotions of cancer patients’ family members are used in the model, including: (1) positive emotion-focused coping strategies; (2) negative emotion-focused coping strategies; (3) positive action-focused coping strategies; (4) negative action-focused coping strategies.

Increased demand for transportation is inevitable along with the growth of social welfare and economic development. Furthermore, providing cheap transportation services has brought about a bulk of benefits in the ever-expanding development of countries. Therefore, the optimization of fuel consumption in the transportation sector is essential for the continued low cost of transportation and reduced amount of pollution caused by the traffic. A major strategy for optimizing fuel consumption and transportation costs in the transportation of goods and passengers is the proper design of transportation networks. Accordingly, in this study, hub covering location problem is modeled taking into account the queuing system in order to minimize the cost of the whole network as well as to minimize emissions of greenhouse gases. The model presented in this study includes uncertain parameters of demand and transportation costs. To control the parameters, a robust-box optimization method is used. As the hub covering network model is multi-objective and NP-hard, three meta-heuristic algorithms; namely MOPSO, NSGA II and MOALO are presented. Computational results show the high efficiency of the MOALO algorithm for obtaining efficient problem-solving in large sizes.

Distribution centers selection is a vital task of any company to reduce costs, improve efficiency of transport flows, which yields customer satisfaction. To select the suitable distribution centers, many quantitative and qualitative criteria must be considered in the selection process. Therefore, distribution centers selection can be seen as a multi-criteria decision making (MCDM) problem under vague environment. Single-valued complex neutrosophic sets (SVCNSs), which is generalized of fuzzy sets, complex fuzzy sets and intuitionistic fuzzy sets; can better represent the vague information than the other sets. This paper aims to propose a new the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) approach based on SVCNSs to select the locations of distribution center. In the proposed TOPSIS approach, the importance weights of criteria, the ratings of alternatives, and their aggregated values are assessed and evaluated using SVCNSs. Then, this paper defines the operational rules of SVCNSs and calculates the aggregated weighted ratings of alternatives. Furthermore, the score, accuracy and certainty function are developed to rank the alternatives. Last, an application to the distribution center location selection is presented to show the advantages of the proposed approach.

Synthesis of 1, 2-disubstituted benzimidazoles by reaction of N-substituted benzene-1,2-diamine with different aldehydes was developed. This greener procedure proceeds with the help of oxygen in water at 60oC. The advantages of proposed method are catalyst-free conditions in water, short reaction time and excellent yields.

In this study, a green and practical approach towards Hantzsch dihydropyridine synthesis of acridine-1,8-diones is introduced. Via the mentioned protocol, the one-pot condensation reaction of structurally diverse aromatic aldehydes, dimedone and NH4OAc was promoted by microwave radiation at solvent and catalyst-free conditions. Consequently, acridinedione products were produced in 81‒97% yields within 3‒8 min. The current protocol represents the prominent advantages in terms of the using a simple synthetic procedure, short reaction times, mild reaction conditions, high yield of the products as well as omission of hazardous and cost-effective organic solvents/reagents.

Seafood processing operations generate a high strength wastewater, which contain organic pollutants in soluble, colloidal, particulate form and salt content, up to 30g NaCl/L. This research aimed to study the effect of salt (NaCl) concentration on the treatment efficiency of seafood processing wastewater by the use of a laboratory-scale bioreactor, which is operated in anaerobic combining aerobic system with concentration salt different from 0- 5%. The results showed that the wastewater from seafood processing with the chemical input parameters of pH = 7 - 8.5, COD = 2000 mg / L, total nitrate nitrogen = 150 mg / L, NH⁴⁺ = 90 mg / L, total phosphorus = 50 mg / L, salt content 3% was treated with anaerobic activated sludge content of 8000mg/l, 16HRT and combining an aerobic activated sludge content of 6000mg/l, 6HRT, DO=2-4mgO₂/l with the acclimatization of 7% bacteria Bacillus velezensis at high salinity The parameters output wastewater was treated according to standards QCVN 11-MT:2015/BTNMT (column B).