Archive of

Advanced Engineering Science

Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-02-10-2022-342

Abstract : Additive Manufacturing (AM) has been a frontier topic in the industrial revolution 4.0. Out of several AM techniques, fused deposition modeling (FDM) is the most widely used technique. FDM uses filament as input feeding. The dimensional accuracy of the filament is an essential factor for success in this method. This research is an attempt to fabricate a filament made of polypropylene using a plastic extrusion machine. According to the typical FDM type 3D printer, the target is a filament with a diameter of 1.75 mm. The three main parameters that affect the dimensional accuracy of the filament are varied, namely the heating band temperature band (150-170 oC, 155-175 oC, and 160-180 oC), winding speed (13 mm/s, 16 mm/s, and 19 mm/s), the distance between the roll and the nozzle (200 mm, 500 mm and 700 mm). The experiment was designed according to the Taguchi L9. Minitab 19 was used to determine the S/N ratio and analyze the variance (ANOVA). It proved that temperature and distance significantly affect the diameter of the extruded filament while rolling speed does not significantly affect the filament diameter. Applying a combination of temperature (160-180 oC), nozzle to a winding distance of 700 mm), and rolling speed of 13 mm/s would achieve the best accuracy of filament diameter of 1.73 mm with a deviation of 0.03 mm..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-28-09-2022-336

Abstract : The oil and gas processing plant is a chaotic network of equipment, piping networks, Infrastructure etc. Cost control and cost-effective maintenance of machines with lower breakdowns of equipment and piping systems increase the enterprise's production. How malfunctions affect capacity, quality, and operating cost. Choosing the right maintenance policy in a wide range of maintenance policies generates profits. In this paper, A case study of Production operations (Maintenance) is conducted to identify Division wise pre-planned maintenance (PPM) and Shut down Maintenance (SM) parts, together and compare them with the cost-benefit analysis model. However, crafting a maintenance strategy depends on some factors, including downtime cost, reliability characteristics, and asset duplication. Thus, the balance between Division wise PPM and SM to reduce costs between institutional equipments and assets. Studies on the relationship between PPM and SM costs have been studied in this article by analyzing historical data. Statistics of the study results show that PPM benefit is positive and more beneficial with the benefit to cost ratio and its comparison with Shut down maintenance. At the same time, increase the operating plant availability and productivity. However, the results depend on including / excluding user costs, as well as individual oil and gas regulatory parameters..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-28-09-2022-333

Abstract : Cloud computing is one of today's most hotly debated research areas because of its capacity to cut computing costs while simultaneously boosting computing service scalability and flexibility. A major advantage of cloud computing is that users can access shared resources such as software and information whenever and wherever they need it. Cloud computing is now being used in a wide variety of settings, including the military, hospitals, industry, and educational institutions, to store massive amounts of data. The data or information can be retrieved from the cloud at the request of the client. Information can be classed as private, public, or sensitive and all cloud-based information is stored elsewhere. For confidential and personal data, third-party cloud providers are always difficult to trust. Even the cloud industry's biggest players agree that security is a shared duty between the enterprise and the customer. As a result, from the perspective of the client, information stored in the cloud should be encrypted thoroughly to ensure that it cannot be read by any other user. So many difficulties arise when data is stored in the cloud, including the security of that data. Many algorithms have been devised to address these problems. The use of cryptographic techniques in this study helps to alleviate security concerns. For data security, cryptography techniques are becoming more prevalent. Asymmetric Key Cryptography with Related Key Set (AKC-RKS) technique is used in this paper to give novel safety mechanisms. The proposed model is compared with the traditional encryption techniques and the results show that the data security levels of the proposed model is high..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-28-09-2022-331

Abstract : Chalcone and its derivatives are known for their biological activities such as antibacterial, anticancer, antioxidant, and anti-inflammatory. This research conducted a synthesis of chalcone derivatives, namely 4-dimethylamino-4-hydroxy chalcone (DMAHC), 4-dimethylamino benzal acetone (DMAB), and 6-fluoro-2-chloro-4-hydroxy chalcone (FCHC) by grinding technique. The grinding technique was successfully carried out with zero solvents to minimize waste production. Claisen-Schmidt condensation reaction with NaOH as a base catalyst was employed in this study to synthesize chalcone compounds. The grinding process was succesfully applied in a very short time, approximately 15 minutes. The derivative products, DMAHC, DMAB, and FCHC, were produced in the form of yellow solids with melting points of 67, 65, and 189°C with yields of 46.32, 33.49, and 26.55%, respectively. FTIR spectrophotometer characterized a sharp absorption in around 1660 cm-1 as a typical absorption of the C=O carbonyl functional group of chalcone derivatives. The analysis results with 1H-NMR showed the appearance of proton absorption in the chemical shift (δ) between 7.6 and 7.8 ppm as the proton absorption of the alkene group (-CH=CH-) from chalcone derivatives..
Full article
Gongcheng Kexue Yu Jishu/Advanced Engineering Science
Journal ID : AES-27-09-2022-330

Abstract : Preventing suicide before it happens, is one of the most challenging tasks for the police force as well as family members. Observed main reasons behind incidents of suicide cases are daily personal lifestyle, working condition, social life behavior and person’s depression condition. According to recent studies, examining the effects of social interactions and context practices on various modes of expression, such as visual, textual, and social activity using social media is possible to be used to predict depression signs. The paper has put forward elements of reviewing initial studies on social media depression detection. Four digital libraries were searched for primary studies: ScienceDirect, SpringerLink, IEEE Xplore Digital Library and Association for Computing Machinery (ACM) Digital Library to broaden the results. The technique of this study is to review each article. Twenty-eight initial studies were examined. In the conclusion of this study, geotagging is the most analyzed social media platform technique to find locations shared by people. Hashtags were the most applied for depression detection. Rule-based sentiment analysis can grasp phrases that contain sarcasm to detect depression. Multimodal features such as users’ comments and image posts with machine learning or deep learning acquire the best output results to detect depression..
Full article

Journal Visit

Top Visit

Medium Visit

Less Visit

Not Visit