The wastewater treatment plant is an extremely important infrastructure to ensure the quality of life, water use of human life, and other ways to ensure water quality for the natural environment. In the operation of it, there are always potential hazards affecting the health of the workers working in the factory. The study was performed using the Semi-quantitative risk assessment method to calculate the values of operational risks in the water treatment plant (WWP). The results of the study obtained 18 high potential hazards that may lead to the present in the water treatment process. The hazards were the leakage of deodorizing towers and the generation of toxic emissions of dead microorganisms that have the highest value with a risk scale of 20 points- frequent impacts on employees. The study has also identified the dangers present in WWP and this will be the premise for mitigating solutions for problems occurring at its.

Environmental issues such as the wastewater have influenced each aspect of our lives. For human and environmental health protection, it is necessary to remove excess zinc in industrial wastewaters before discharging them to environment. Modified diatomite displayed larger surface area and pore volumes in comparison with untreated natural diatomite, which favored heavy metals sorption behavior. In this study, the removal of Zn(II) ions from aqueous solution was studied using Fe/Mn modified diatomite sample at different adsorption parameters such as contact initial metal ions concentration, dosage of Fe/Mn-Diatomite and ionic strength Na2CO3 on ionic Zn2+ adsorption capacity of diatomite modified. The residual zinc concentration in the solution was determined using flame atomic absorption spectroscopy. The results showed that: the gravitational increase increases with increasing time and then becomes almost stable, with 120 minutes timeliness; absorption increases when Fe/Mn-Ditomite is increased, absorption reaches 89.48% at a dose of 1.5 g/l; additional different concentrations Na2CO3 ranged from 0 ppm to 80 ppm the results showed that performance treatment Zn2+ of correspond 94,85%. This study could lay an essential foundation to develop modified diatomite for heavy metal removal from wastewater.

Bien Hoa City is an urban area of Dong Nai province located in the Southern key economic region. Currently, Bien Hoa City has 6 industrial parks in operation with large daily wastewater flow, causing environmental risks, especially from organic pollutants. The study applied the Nemerow risk index and the geographic information systems (GIS). The results showed that the industrial parks were mainly organic pollution levels including N-total, P-total, and Ammonium. The level of environmental risk from organic pollution was recorded in range of medium to very high levels, the ranked in descending order: Agtex Long Binh Industrial Park (P = 24)> Amata Industrial Park (P = 16)> Bien Hoa 2 Industrial Park ( P = 10),> Tam Phuoc Industrial Park (P = 5)> Loteco Industrial Park (P = 3). The results of the study provided good information for the management and improvement of wastewater quality in the industrial wastewater treatment plants of the industrial parks in Bien Hoa City.

Along with changes in Economy, Tourism and the influence of foreign waves, the market of Food Service in Vietnam has also changed to meet the needs of customers. At many restaurants in Vietnam, customer satisfaction can greatly affect restaurant revenue. Therefore, it is essential to determine which perceived quality factors affect customer satisfaction. The survey was conducted through questionnaires collected from 329 respondents, who experienced in restaurant services in Vietnam. In this paper, four factors are found that have influence on customer satisfaction in restaurants: Service quality, Product quality, Environment and Price. In addition, the research also gives some contributions based on the research results, helping businesses understand customers and meet customer satisfaction requirements in the restaurant.

Activity recognition is one of the preliminary steps in designing and implementing assistive services in smart homes. Such services help identify abnormality or automate events generated while occupants do as well as intend to do their desired Activities of Daily Living (ADLs) inside a smart home environment. However, most existing systems are applied for single-resident homes. Multiple people living together create additional complexity in modeling numbers of overlapping and concurrent activities. In this paper, we introduce a hybrid mechanism between ontology-based and unsupervised machine learning strategies in creating activity models used for activity recognition in the context of multi-resident homes. Comparing to related data-driven approaches, the proposed technique is technically and practically scalable to real-world scenarios due to fast training time and easy implementation. An average activity recognition rate of 95.83% on CASAS Spring dataset was achieved and the average recognition run time per operation was measured as 12.86 mili-seconds.

Corrosion of the bottom of the petroleum tank may lead to a product leak that could cause a fire or explosion resulting in damage to people and the environment, therefore the test of tank bottom corrosion is necessary to be conducted periodically to prevent the occurrence of the above problems. In non-destructive inspection, the Magnetic Flux Leakage (MFL) method relies on the variation of fluxes caused by defects on the surface of materials to detect corrosion, pitting, or imperfections, which is proved quite effectively with low cost. The project was implemented to develop a prototype of the MFL bottom detection device based on the research results in the world to improve corrosion survey capacity in industrial equipment, as well as to improve the expertise in the Research Team of electronics and automation in the fields of magnetic fields and sensors. As a result, an MFL model using permanent magnets and Hall sensors were fabricated. Survey experiments showed that the machine could detect corrosion defects up to 20% of steel wall thickness in the scanning speed range from 500 mm/s to 1130 mm/s. However, to meet the actual survey needs, the team must continue to improve the device in terms of sensitivity, scanning speed, the ability to operate automatically or semi-automatically, and register for a fire safety inspection.

Measuring environmental protection activities is a matter of great concern over the years. In this study, the indicators for evaluating environmental protection activities in industrial parks was built according to the PDSIR model and based on Vietnam's legal framework, including 18 main subjects and 35 indicators. The environmental performance index of industrial park (EPIIP) was established based on the multi-criteria evaluation method and the analytic hierarchy process method. The results of the study indicated that the VSIP I industrial park reached 68.95 points (relatively good level). Moreover, the results also showed that VSIP I was one of the industrial parks practicing good performance to protect environmental problems.

Nowadays, the benefits of ISO 14001:2015 abound, for minimizing environmental footprints, providing operational improvements, bringing lucrative business and improving the company’s image. There is an annual audit to decide if the company’s environmental management system meets the requirements of ISO 14001:2015. This is a significant audit that strongly affects the current certificate. The study to “Evaluate the efficiency of the environmental management system ISO 14001:2015 at the Vietnam Onamba Company” has been conducted to research the internal audit and examine any discordance in the environmental management system. The study carries out the internal audit of the environmental management system ISO 14001:2015 at VTO company by 3P method (P1: Paper check, P2: People interview, P3: Practice Observe). The result of the study showed a minor discordance at (6.2) Environmental Objectives and planning to achieve them. Regarding other clauses, they meet the requirements of the environmental management system. The result shows that the responsibility and careful observation of the company in controlling the system. The study evaluates reducing consumption (electricity, water, and chemicals) through collecting and comparing the data between 2017 and 2018. The results show the efficiency of reducing consumption: monthly electricity consumption reduced 21,86% (377 MWh); monthly water usage reduced 17,89% (1421 m3 ); annual chemical usage reduced from 3 to 6%.