Recent Application of Bio-Alcohol: Bio-Jet Fuel

Recently, the biomass-based energy production has been actively studied as a research and development area for reducing carbon emissions as a solution to global warming caused by the increase of carbon dioxide emissions. Especially, as the energy consumption in the air transportation field increases, the carbon dioxide emissions increase simultaneously. Therefore, the bio-jet fuel production technology is being actively developed to solve this problem. The bio-jet fuel manufacturing process is a process of manufacturing biomass-derived jet fuel that can replace the existing petroleum-based jet fuel. It includes an alcohol-to-jet (ATJ) process using bio-alcohol such as bio-butanol and bio-ethanol, oil-to-jet (OTJ) process using vegetable oil, and an F-T process using syngas obtained from gasification of biomass-based raw materials

Design of Orientation-Free Handler and Fuzzy Controller for Wire-Driven Heavy Object Lifting System

This paper presents an intention interface and controller for a wire-driven heavy object lifting system that assists the operator with moving a heavy object. The handler is designed to allow a comfortable working posture for the operator. Plus, as a human assistive system, the operator is involved in the control loop, where a fuzzy control system is used to consider the human control characteristics. The effectiveness and performance of the proposed system are proved by experiments

Lightweight Image Inpainting by Stripe Window Transformer with Joint Attention to CNN

Image inpainting is an important task in computer vision. As admirable methods are presented, the inpainted image is getting closer to reality. However, the result is still not good enough in the reconstructed texture and structure based on human vision. Although recent advances in computer hardware have enabled the development of larger and more complex models, there is still a need for lightweight models that can be used by individuals and small-sized institutions. Therefore, we propose a lightweight model that combines a specialized transformer with a traditional convolutional neural network (CNN). Furthermore, we have noticed most researchers only consider three primary colors (RGB) in inpainted images, but we think this is not enough. So we propose a new loss function to intensify color details. Extensive experiments on commonly seen datasets (Places2 and CelebA) validate the efficacy of our proposed model compared with other state-of-the-art methods. Index Terms: HSV color space, image inpainting, joint attention, stripe window, transformerComment: 6 pages and 5 images, contributions to MLSP 202

Dynamics of Dark Web Financial Marketplaces: An Exploratory Study of Underground Fraud and Scam Business

The number of Dark Web financial marketplaces where Dark Web users and sellers actively trade illegal goods and services anonymously has been growing exponentially in recent years. The Dark Web has expanded illegal activities via selling various illicit products, from hacked credit cards to stolen crypto accounts. This study aims to delineate the characteristics of the Dark Web financial market and its scams. Data were derived from leading Dark Web financial websites, including Hidden Wiki, Onion List, and Dark Web Wiki, using Dark Web search engines. The study combines statistical analysis with thematic analysis of Dark Web content. Offering promotions and customer services with the payment methods of cryptocurrencies were prevalent, similar to the Surface Web\u27s e-commerce market. The findings suggest that the Dark Web financial market is likely to harbor scams targeting Dark Web buyers. Dark Web sellers construct a website to sell scam products and recommend purchasing Escrow services to ensure safe transactions as an additional scam. The results from this study provided empirical support for the components of the routine activity theory of the Dark Web financial market to substantiate a more comprehensive view of patterns of fraud/ scams. Enhancing law enforcement capabilities of investigating financial marketplaces and promoting public awareness and consumer safety programs are discussed as effective preventive measures

Prediction Data Processing Scheme using an Artificial Neural Network and Data Clustering for Big Data

Various types of derivative information have been increasing exponentially, based on mobile devices and social networking sites (SNSs), and the information technologies utilizing them have also been developing rapidly. Technologies to classify and analyze such information are as important as data generation. This study concentrates on data clustering through principal component analysis and K-means algorithms to analyze and classify user data efficiently. We propose a technique of changing the cluster choice before cluster processing in the existing K-means practice into a variable cluster choice through principal component analysis, and expanding the scope of data clustering. The technique also applies an artificial neural network learning model for user recommendation and prediction from the clustered data. The proposed processing model for predicted data generated results that improved the existing artificial neural network–based data clustering and learning model by approximately 9.25%

Stress and vibration of a viscoelastic damping isolator under impact loading

There are different types of isolators which include rubber type, coil spring type, slide and rotating type and there are different types of dampers which include viscous type, oil type, and try friction type. Both isolators and dampers are common used to reduce vibration caused by forging or stamping process. However, a new way to reduce the vibration of the punch press is viscoelastic damping isolator (VDI) which can be widely used in manufacturing, electricity and gas supply, construction, transportation and warehousing, and other industries. This study analyzes a VDI composed by partitions, damping fluid, steel springs and level adjusters. Different numbers of the partitions are welded on upper and lower rectangular steel plates, respectively. Up to 150 tons of weight of the punching machines supported by steel springs which are placed at the edges between the square upper/lower plates. Screw types of level adjusters are placed between lower plate and thick steel base to tune the horizontal level of the isolator. High viscosity damping fluid is filled in the space between interlacing partitions around 60 % of the height of the VDI. Punching induced impact energy is dissipated by shear deformation between the damping fluid and partitions. This study uses 3D graphing software and finite element method (FEM) to investigate the dynamic characteristic of the damping isolator after impacted by the puncher. The normal mode analysis of the VDI is obtained. The isolator is settled within 0.3 seconds after 300.000 N of shock impact and satisfies industrial specification of large punchers with loading frequency of 100 cycles per min