• The KIPS Transactions:PartC
• /
• v.12C no.4 s.100
• /
• pp.559-570
• /
• 2005

ECN is accurate in determining traffic congestion since it explicitly notifies the incipient congestion. Therefore, ECN method has been thoroughly studied in the field of wireless TCP. This paper introduces a formula to find the optimal threshold for ECN marking. We have implemented a Petri net model of 'TCP with ECN strategy' and performed simulations on it in order to verify the validity of the formula. We have also introduced ideas of applying the formula in practice. The primary contribution of this paper is proposing a formula to find the optimal threshold for ECN marking. However, introducing the Petri net model of 'TCP with ECN strategy' is no less valuable contribution because it can be helpfully used by the researchers in studying network protocols. We have built the Petri net model by modifying the existing Petri net model of TCP. In order to add ECN strategy to the existing model, we have mainly modified the network part. We have also modified sender part and receiver part as well.

• Korean Journal of Fisheries and Aquatic Sciences
• /
• v.18 no.3
• /
• pp.214-218
• /
• 1985

A survey was made to determine seasonal variation of histamine, total volatile base and trimethylamine levels in a number of fresh fish and canned fish products as available through present distribution systems in Seoul area in order to assess potential danger of histamine poisoning related problems. Data obtained indicated that those products as available in present distribution systems should present no potential danger of histamine poisoning related problems.

• The KIPS Transactions:PartB
• /
• v.9B no.1
• /
• pp.77-82
• /
• 2002

Progressive image transmission involves a progressive increase in the image resolution at the receiver from a lower to a higher resolution during the transmission of data. This is an effective way of using a limited transmission channel, because, after estimating the value of the data in the early transmission period, a decision can be made whether or not to proceed with the transmission of the remaining part. To realize more effective progressive image transmission, the current thesis divides an image into bit planes and then re-organizes each plane into a complementary quadtree structure. As a result, by transmitting the data on each bit plane and each level of the complementary quadtree in the appropriate order, the basic image contents can be understood with less data in the early period of transmission.

• Journal of Digital Contents Society
• /
• v.18 no.8
• /
• pp.1635-1640
• /
• 2017

In this paper, a hierarchical image tree model for weather classification is defined in a single outdoor image, and a weather classification algorithm using image intensity and k-mean segmentation image is proposed. In the first level of the hierarchical image tree model, the indoor and outdoor images are distinguished. Whether the outdoor image is daytime, night, or sunrise/sunset image is judged using the intensity and the k-means segmentation image at the second level. In the last level, if it is classified as daytime image at the second level, it is finally estimated whether it is sunny or foggy image based on edge map and fog rate. Some experiments are conducted so as to verify the weather classification, and as a result, the proposed method shows that weather features are effectively detected in a given image.

• Journal of Korean Society of Coastal and Ocean Engineers
• /
• v.34 no.3
• /
• pp.47-57
• /
• 2022

We carried out studies on prediction in concentration of dissolved oxygen (DO) with LSTM model and prediction in occurrence of hypoxia water mass (HWM) with decision tree. As results of study on prediction in DO concentration, a large number of Hidden node caused high complexity of model and required enough Epoch. And it was high accuracy in long Sequence length as prediction time step increased. The results of prediction in occurrence of HWM showed that the accuracy of nonHWM case was 66.1% in 30 day prediction, it was higher than 37.5% of HWM case. The reason is that the decision tree might overestimate DO concentration.

• Journal of The Korean Association of Information Education
• /
• v.24 no.5
• /
• pp.483-494
• /
• 2020

With the advent of the 4th Industrial Revolution, interest in AI education is increasing. In order to cultivate talented people with AI competencies who will lead the future, AI education must be conducted in a sound manner at the school site. Although AI education is being conducted at home and abroad, it was determined that the role of the AI education platform is important to implement better AI education, so this study investigated the perception of experts on the AI education platform. A perception survey was conducted based on five criteria: teaching and learning management, educational contents, accessibility, performance of AI education platform, and level suitability of elementary school students. As a results, the number of 103 educational experts selected 'Entry' as the most proper platform among the eight platforms - 'Machine learning for Kids', 'Teachable Machine', 'AI Oceans(code.org)', 'Entry', 'Genie Block', 'Elice', 'mBlock' and etc. Analysis shows that this is because 'Entry' provides quality educational content, has convenient accessibility, is easy to manage teaching and learning, as well as an AI education platform suitable for the level of elementary school. In order to apply various AI education platforms to the school field, it is necessary to train teachers in AI-related training to train them as AI education experts, and to continuously provide opportunities to experience AI education platforms. In this study, there are limitations to what is called 'a population perception survey'. because only 103 people were surveyed, and most of the experts are working in a specific area(Gyeonggi-do). In the future, it is judged that research targeting experts at the national level should be conducted to supplement these limitations.

• Korean Journal of Food Science and Technology
• /
• v.50 no.4
• /
• pp.420-429
• /
• 2018

Skin ageing is associated with compromised performance of its fundamental barrier functions, with undesirable changes in appearance. Since this may introduce a detrimental impact on the quality of life, significant effort to discover effective ingredients against ageing is being invested. Recently, collagen hydrolysates containing tripeptides such as GlyPro-Hyp (GPH) have been developed with anticipation of improved effects compared to that of existing collagen hydrolysate-products. To evaluate the cutaneous hydration effect of collagen tripeptides (CTP), meaningful biomarkers in human dermal fibroblasts (HDF) and NC/Nga Tnd mice were analyzed in this study. Increased levels of ceramide kinase, hyaluronic acid, collagen 1A, and hyaluronan synthase-2 (HAS2), and decreased levels of hyaluronidase-1 (HYAL1) and CD44 in HDF cells were demonstrated. Furthermore, significant reduction of transepidermal water loss (TEWL), scratching behavior, HYAL1, $TNF-{\alpha}$ and IL-6 and increased water content and HAS2 were verified by in vivo tests. These results strongly suggest the potential of CTP as a skin hydration agent.

• Journal of The Korean Association of Information Education
• /
• v.24 no.5
• /
• pp.473-481
• /
• 2020

Data science starts with small data analysis and includes machine learning and deep learning for big data analysis. Data science is a core area of artificial intelligence technology and should be systematically reflected in the school curriculum. For data science education, The Entry also provides a data analysis tool for elementary education. In a big data analysis, data samples are extracted and analysis results are interpreted through statistical guesses and judgments. In this paper, the big data analysis area that requires statistical knowledge is excluded from the elementary area, and data science education examples focusing on the elementary area are proposed. To this end, the general data science education stage was explained first, and the elementary data science education stage was newly proposed. After that, an example of comparing values of data variables and an example of analyzing correlations between data variables were proposed with public small data provided by Entry, according to the elementary data science education stage. By using these Entry data-analysis examples proposed in this paper, it is possible to provide data science convergence education in elementary school, with given data generated from various subjects. In addition, data science educational materials combined with text, audio and video recognition AI tools can be developed by using the Entry.

• Proceedings of the Korean Information Science Society Conference
• /
• 2012.06b
• /
• pp.468-470
• /
• 2012

본 논문에서는 기존 VectorBoost기반 분류기의 문제점이었던 다중 분할 노드에서의 오판단 발생을 해결하기 위해, LDA를 이용해 학습 샘플들을 가장 잘 분리할 수 있는 최적의 초평면을 구하고, 이 초평면을 이용해 Positive샘플에서 VectorBoost의 판단율을 향상시키는 방법을 제안한다. 이러한 방법을 적용했을 때 Positive샘플들의 오판단율이 감소하는 효과를 보였으며, 불필요한 연산의 감소로 약 30%의 속도향상을 얻을 수 있었다.

• Korean Journal of Agricultural Science
• /
• v.35 no.1
• /
• pp.101-118
• /
• 2008

This paper reviews the present situation of Triticale cultivation and examines the potentiality of contribution to livestock as well as poultry sector in Bangladesh Agriculture. Triticale is a human-made cross between rye and durum wheat that has the ability to produce quality green fodder, and then re-grow after first and second cutting to produce grain. In Bangladesh, it is a non-traditional cereal that grows well during the cool and dry Rabi season (November-March) when fodder and feed scarcity is a major limiting factor for ruminant livestock. In Bangladesh Triticale was started to grow in the late Ninety's. The scientists of Bangladesh Agricultural Research Institute (BARI) were first introduced triticale in Bangladesh. Still now the situation of Triticale is grown as fooder and feed in Bangladesh within the scientists under trial. High quality grass fodder was obtained by cutting green triticale plants twice, at 35 and 50 days after seeding, while later the ratooning tillers produced grain to a yield of 1.1-2.4 t/ha of grain for poultry feed or human food. Triticale straw was twice as nutritious as rice or wheat straw and its grain contained more protein than other cereals. Researchers and farmers have also successfully made triticale hay and silage from a mixture of triticale green cuttings, rice straw and molasses. A feeding trial at Bangladesh Livestock Research Institute(BLRI), Savar station showed a large(46%) increase in cow live weight gain and a 36% increase in milk yield (but no change in milk quality or dry matter intake) in cows fed triticale silage compared with those fed rice straw over a period of nine weeks. In another feeding trial, it was found that triticale grain was a good replacement for wheat in the feed blend for chickens in Bangladesh. So it will be a good chance to alive our livestock as well as poultry sector if triticale enters to our existing cropping system as fodder cum grain. The challenge in Bangladesh is to identify fodder technologies that match existing small-scale farmer cropping patterns without needing major inputs or increasing risks. Preliminary field experiments revealed that triticale is a crop with good potential to produce quality fodder and grain for small scale farmers in Bangladesh.