In recent years, importance of blockchain systems has been grown after success of bitcoin. Distributed consensus algorithm is used to achieve an agreement, which means the same information is recorded in all nodes participating in blockchain network. Various algorithms were suggested to resolve blockchain trilemma, which refers conflict between decentralization, scalability, security. An algorithm based on Byzantine Agreement among Decentralized Agents (BADA) were designed for the same manner, and it used limited committee that enables an efficient consensus among considerable number of nodes. In addition, election of committee based on Proof-of-Nonce guarantees decentralization and security. In spite of such prominence, application of BADA in actual blockchain system requires further researches about performance and essential features affecting on the performance. However, performance assessment committed in real systems takes a long time and costs a great deal of budget. Based on this motivation, we designed and implemented a simulator for measuring performance of BADA. Specifically, we defined a simulation framework including three components named simulator Command Line Interface, transaction generator, BADA nodes. Furthermore, we carried out response surface analysis for revealing latent relationship between performance measure and design parameters. By using obtained response surface models, we could find an optimal configuration of design parameters for achieving a given desirable performance level.

Recently, blockchain technology has been recognized as one of the most important issues for the 4th Industrial Revolution which can be represented by Artificial Intelligence and Internet of Things. Cryptocurrency, named Bitcoin, was the first successful implementation of blockchain, and it triggered the emergence of various cryptocurrencies. In addition, blockchain technology has been applied to various applications such as finance, healthcare, manufacturing, logistics as well as public services. Distributed consensus algorithm is an essential component in blockchain, and it enables all nodes belonging to blockchain network to make an agreement, which means all nodes have the same information. For example, Bitcoin uses a consensus algorithm called Proof-of-Work (PoW) that gives possession of block generation based on the computational volume committed by nodes. However, energy consumption for block generation in PoW has drastically increased due to the growth of computational performance to prove the possession of block. Although many other distributed consensus algorithms including Proof-of-Stake are suggested, they have their own advantages and limitations, and new research works should be proposed to overcome these limitations. For doing this, above all things, we need to establish an evaluation method existing distributed consensus algorithms. Based on this motivation, in this work, we suggest and analyze assessment items by classifying them as efficiency and safety perspectives for investigating existing distributed consensus algorithms. Furthermore, we suggest new assessment criteria and their implementation methods, which can be used for a baseline for improving performance of existing distributed consensus algorithms and designing new consensus algorithm in future.

The International Organization for Standardization (ISO) published ISO 9001 Quality Management System (QMS)-Requirements in 1987 and has revised four times since then. ISO 9001:2015 is the latest edition. This latest edition has two most noticeable changes. The first major change of new edition focuses on performance with an emphasis on Risk-Based Thinking (RBT) to enhance the process approach. The new edition consists of ten clauses whose first three clauses are largely same as older edition but risks are clearly stated and stressed in last seven clauses, emphasizing on Plan-Do-Check-Act cycle at all levels in the organization. The second major change is that the new edition has the same overall structure as other ISO management system standards known as High Level Structure (HLS) with Annex SL. The companies obtained the certificate of new ISO 9001:2015 QMS by September 15, 2018 in order to maintain as an ISO QMS registered firm. In this article we collected transition audit data from more than 100 companies that registered ISO 9001:2015 QMS for recent three years. We performed a statistical analysis to disclose the relationships between the characteristics of companies and the minor nonconformities found in ISO 9001:2015 requirements during transition audit processes. We also aim to interpret the findings and deduce the implications of the statistical results.

In recent years, imbalanced data is one of the most important and frequent issue for quality control in industrial field. As an example, defect rate has been drastically reduced thanks to highly developed technology and quality management, so that only few defective data can be obtained from production process. Therefore, quality classification should be performed under the condition that one class (defective dataset) is even smaller than the other class (good dataset). However, traditional multi-class classification methods are not appropriate to deal with such an imbalanced dataset, since they classify data from the difference between one class and the others that can hardly be found in imbalanced datasets. Thus, one-class classification that thoroughly learns patterns of target class is more suitable for imbalanced dataset since it only focuses on data in a target class. So far, several one-class classification methods such as one-class support vector machine, neural network and decision tree there have been suggested. One-class support vector machine and neural network can guarantee good classification rate, and decision tree can provide a set of rules that can be clearly interpreted. However, the classifiers obtained from the former two methods consist of complex mathematical functions and cannot be easily understood by users. In case of decision tree, the criterion for rule generation is ambiguous. Therefore, as an alternative, a new one-class classifier using hyper-rectangles was proposed, which performs precise classification compared to other methods and generates rules clearly understood by users as well. In this paper, we suggest an approach for improving the limitations of those previous one-class classification algorithms. Specifically, the suggested approach produces more improved one-class classifier using hyper-rectangles generated by using Gaussian function. The performance of the suggested algorithm is verified by a numerical experiment, which uses several datasets in UCI machine learning repository.

There are three kinds of Pleurotus eryngii : P. eryngii var. eryngii (P. eryngii), P. eryngii var. ferula (P. ferula : A-Wei-Mo) P. eryngii var. nebrodensis (P. nebrodensis : Bai-Ling-Gu). We bred P. ferula using Di-Mon mating and physiological assay and selected as follow (1) ‘Beesan No.1’ produced high yields, (2) ‘Beesan No.2’ was excellent morphological shape and anti-adipogenic Activit, (3) ‘Ergo’ included high ergothioneine such as anto-oxidant material, (4) ‘GW10-45’ included highest ergothioneine such as anto-oxidant material, (5) ‘Maeksong’ included high ergothioneine and effect of anti-inflammatory. We suggest that there are able to food-medicine materials.

Environmental pollution including air, land, and water has become one of the most critical issues in global interest. The damages due to environmental pollution lead to serious disasters. Nations have realized the importance of environment protection and have been starting to force organizations to implement environmental management system (EMS) as way of protecting environment. ISO 14001 requirements that are the most popular standard as EMS have been developed to support continuous improvement to environment management. It has been revised once since publication and ISO 14001 : 2004 version is currently available. Organizations globally started to acquire the certificate of EMS to observe environment related laws, accept customers’ and stakeholders’ request, increase market share, and fulfill implementation motives. This article examines the audit data that were collected for several years from manufacturing companies including shipbuilding, machinery, metal, automobiles, and chemical companies in southeastern Korea on the basis of ISO 14001 : 2004 requirements. The audit data were classified into minor nonconformities based on factors such as business size, business type, and EMS implementation period. We conduct hypotheses test using statistical methods in order to see if there are any significant differences based on the factors. We draw conclusions for the results of hypotheses test and address the necessities of energy, greenhouse gas, green management, and continuous improvement to enhance the efficiency of EMS implementation.

The objective of this study was to determine the mitotic intervals (τ0) of two consecutive cell divisions and synchronous embryonic cleavage in grass puffer, Takifugu niphobles at different water temperatures (18, 20, 22, and 24℃). The color of the fertilized egg was light yellowish. The egg type was demersal and unadhesive. Egg weight was 0.09±0.002 mg. The sizes of unfertilized eggs were smaller than fertilized eggs in major axis and minor axis at 20℃ (p<0.05). The size of the fertilized egg of 18℃ water temperature group at the blastodisc stage was the smallest (p<0.05), but no significant differences were observed in the other water temperatures group except 18℃ water temperature group (p>0.05). The first cleavage stages at 18, 20, 22, and 24℃ were at 75, 90, 105, and 120 mins, respectively. As water temperature was increased, embryonic development and formation time of the first cleavage furrow were accelerated. There were negative correlation between τ0 and water temperature for grass puffer (Y=–1.225X+70.05, R2=0.988, n=10, where Y was τ0 and X was temperature). This study confirmed that successful hatching of grass puffer was related to water temperature. Chromosome manipulation will be helpful for this species using cleavage frequency and τ0.

The optimum concentrations of clove oil as an anesthetic for olive flounder (Paralichthys olivaceus) and the stress response of the fish to clove oil anesthesia were determined over a range of water temperatures, and investigated in a simulated transport experiment using analysis of various water and physiological parameters. While the time for induction of anesthesia decreased significantly as both the concentration of clove oil and water temperature increased, the recovery time increased significantly (P<0.05). The plasma cortisol concentration in fish at each temperature increased significantly up to 12 h following exposure (P<0.05), then decreased to 48 h (P<0.05). The DO dissolved oxygen concentrations, pH values, and the fish respiratory frequencies decreased over 6 h following exposure to clove oil in all experimental groups (P<0.05), whereas the NH4 + and CO2concentrations in all experimental groups increased up to 6 h (P<0.05). The pH values and DO concentrations increased with increasing clove oil concentration (P<0.05) in the 6 h following exposure, and the CO2 and NH4 + concentrations and the respiratory frequencies decreased with increasing clove oil concentration (P<0.05). The results of this experiment suggest that clove oil reduced the metabolic activity of olive flounder, thus reducing NH4 + excretion and O2 consumption. In conclusion, clove oil appears to be a cost-effective and efficient anesthetic that is safe for use and non-toxic to the fish and users. Its use provides the potential for improved transportation of olive flounder.