Distributed Authentication Model for Secure Network Connectivity in Network Separation Technology

Considering the increasing scale and severity of damage from recent cybersecurity incidents, the need for fundamental solutions to external security threats has increased. Hence, network separation technology has been designed to stop the leakage of information by separating business computing networks from the Internet. However, security accidents have been continuously occurring, owing to the degradation of data transmission latency performance between the networks, decreasing the convenience and usability of the work environment. In a conventional centralized network connection concept, a problem occurs because if either usability or security is strengthened, the other is weakened. In this study, we proposed a distributed authentication mechanism for secure network connectivity (DAM4SNC) technology in a distributed network environment that requires security and latency performance simultaneously to overcome the trade-off limitations of existing technology. By communicating with separated networks based on the authentication between distributed nodes, the inefficiency of conventional centralized network connection solutions is overcome. Moreover, the security is enhanced through periodic authentication of the distributed nodes and differentiation of the certification levels. As a result of the experiment, the relative efficiency of the proposed scheme (REP) was about 420% or more in all cases.

A robust ethane-selective hypercrosslinked porous organic adsorbent with high ethane capacity

While preferential adsorption of ethane (C2H6) over ethylene (C2H4) is more advantageous in industrial separation technology, most porous materials such as metal-organic frameworks, covalent-organic frameworks, and hydrogen-bonded organic frameworks provide...

Non-microbiological turbidity of beer: Part 2 – a case study

Non-microbial beer turbidity of lager beers often indicates a technological problem. Therefore, the occurrence of permanent haze in filtered and stabilized beer should not be underestimated. In this study, practical examples from industrial breweries, where several types of non-microbiological haze of colloidal were identified, are presented. These examples of haze were caused by slightly different factors, and as a result, they had a different microscopic image. It is often accompanied by mechanical impurities and sometimes by microorganisms that function as nucleation centers. Moreover, a very interesting example of almost brilliant permanent beer haze caused by the destruction of yeast cells with the following pouring intracellular contents of cells into beer is introduced. This phenomenon, which could be called “precedent”, was caused by a bad physiological condition of yeasts cells and inappropriately chosen yeast separation technology.

Coal and Gangue Recognition Method Based on Local Texture Classification Network for Robot Picking

Coal gangue is a kind of industrial waste in the coal mine preparation process. Compared to conventional manual or machine-based separation technology, vision-based methods and robotic grasping are superior in cost and maintenance. However, the existing methods may have a poor recognition accuracy problem in diverse environments since coals and gangues’ apparent features can be unreliable. This paper analyzes the current methods and proposes a vision-based coal and gangue recognition model LTC-Net for separation systems. The preprocessed full-scale images are divided into n × n local texture images since coals and gangues differ more on a smaller scale, enabling the model to overcome the influence of characteristics that tend to change with the environment. A VGG16-based model is trained to classify the local texture images through a voting classifier. Prediction is given by a threshold. Experiments based on multi-environment datasets show higher accuracy and stability of our method compared to existing methods. The effect of n and t is also discussed.

Glucosinolates and Isothiocyantes in Processed Rapeseed Determined by HPLC-DAD-qTOF

Glucosinolates are well known as natural antimicrobials and anticarcinogenic agents. However, these compounds can lose their properties and transform into antinutrients, depending on processing conditions. In addition, the bitterness of some glucosinolate in rapeseed meal can affect the likability of the final product. Therefore, it is important to identify and determine each glucosinolate and its derived form, not just the total glucosinolate content, in order to evaluate the potential of the final rapeseed protein product. This study provides a comprehensive report of the types and quantities of glucosinolates and their derived forms (isothiocyanates) associated with different rapeseed processing conditions. Glucosinolates and isothiocyanates were determined by HPLC-DAD-qTOF. In our study, the enzymatic degradation of glucosinolates by myrosinase was the main factor affecting either glucosinolate or isothiocyanate content. Other factors such as pH seemed to influence the concentration and the presence of glucosinolates. In addition, process parameters, such as extraction time and separation technology, seemed to affect the amount and type of isothiocyanates in the final protein extracts. Overall, both determined intact glucosinolates and their derived forms of isothiocyanates can give different types of biological effects. More studies should be performed to evaluate the impact of glucosinolates and isothiocyanates on human health.

A bio-inspired approach for boosting innovation in the separation technology sector

Because of its size, high segmentation within the global market and challenges driving its development, the separation technology sector could benefit from a bio-inspired approach to innovation to create more efficient and sustainable solutions. The potential for bio-inspired innovation is still largely untapped and Biologically-Inspired Design (BID) methods and tools are still largely underutilised, especially within the industry. A new BID method, called Guild-Based (GB) BID, is proposed to create a database of a large set of biological solutions – identified by a function – where biological information is structured to be more effective and usable within the industrial environment. A database for the separation technology sector has been set up and populated with 118 relevant biological solutions responding to the main function ‘to separate’. The database has been utilised to generate several clusters of solutions depending on the level of detail of the formulated problem. In particular, these include broad design principles of separation, taxonomies of biological solutions for specific separation problems and novel design concepts for two specific separation technologies (a desalination technology and an antibacterial surface). Furthermore, because of a large dataset of biological solutions, the possibility of determining the frequency of occurrence of specific separation strategies in nature can trigger reflections on the impact of existing separation technologies and taking decisions on future related R&D paths. More tests need to be conducted in the industrial environment; however, the results achieved so far indicate that the method proposed can indeed be instrumental to generating innovative ideas of interest to the separation technology sector.