Hybrid nanocomposites of aluminium (NHAMMCs) made from AA5052 are fabricated via stir casting route by reinforcing 12 wt% Si3N4 and 0.5 wt% of graphene for usage in aeronautical and automotive applications due to the lower density and higher strength to weight proportion. The wear characteristics of the NHAMMCs are evaluated for different axial load, rotational speed, sliding distance and sliding time based on Box-Behnken design (BBD) of response surface methodology (RSM). Orowan strengthening mechanism is identified from optical image which improves the strength of the composite. Outcomes show that with higher axial load and rotational speed, there is substantial increase in wear loss whereas with increased sliding distance and sliding time there is no considerable increase in wear loss due to the lubricating nature of the reinforced graphene particles since it has higher surface area to volume ratio. Besides, artificial intelligence approach of neuro-fuzzy (ANFIS) model is developed to predict the output responses and the results are compared with the regression model predictions. Prediction from ANFIS outplays the regression model prediction.

To obtain a license for a deep geological disposal repository for spent nuclear fuel, it is necessary to perform a safety assessment that quantifies the radiological impact on the environment and humans. One of the key steps in the safety assessment of a deep geological repository is the development of scenarios that describe how the repository evolves over the performance period and how events and processes affect performance. In the field of scenario development, demonstrating comprehensiveness is critical, which describes whether all factors that are expected to have a significant impact on the repository's performance have been considered. Mathematical proof of this is impossible. However, If the scenario development process is logical and systematic, it can support the claim that the scenario is comprehensive. Three primary approaches are being considered for scenario development: ‘Bottomup’, ‘Top-down’, and ‘Hybrid’. Hybrid approach provides a more systematic and structured process by considering both the FEPs (Features, Events, Processes) and safety functions utilized in the bottomup and top-down approaches. Many countries that develop recent scenarios prefer demonstrating scenario comprehensiveness using a hybrid approach. In this study, a systematic and structured scenario development process of a hybrid approach was formulated. Based on this, sub-scenarios were extracted that describe the phenomena occurring in the repository over the performance period, categorized by period. By integrating and screening the extracted sub-scenarios, a scenario describing the phenomena occurring over the entire period of disposal was developed.

이 논문에서는 백본 네트워크의 경제적 확장 방법을 제시한다. 기존 연구에서의 네트워크 확장은 기 설치된 네트워크에 새로운 노드를 추가하는 데 그치고 있다. 이 논문에서는 새로운 노드의 추가 외에 기 설치된 링크의 용량 확장 까지를 고려하는 경제적 확장 설계 방법을 제시한다. 경제적 네트워크 확장은기 설치된 네트워크와 perform-ability를 제약조건으로 하면서 비용을 최소화하는 문제로 표현된다. 효율적인 해외 탐색을 위해 이진과 K진이 혼용된 하이

The aim of this paper is to predict the Borsa Istanbul (BIST) 30 index movements to determine the most accurate buy and sell decisions using the methods of Artificial Neural Networks (ANN) and Genetic Algorithm (GA). We combined these two methods to obtain a hybrid intelligence method, which we apply. In the financial markets, over 100 technical indicators can be used. However, several of them are preferred by analysts. In this study, we employed nine of these technical indicators. They are moving average convergence divergence (MACD), relative strength index (RSI), commodity channel index (CCI), momentum, directional movement index (DMI), stochastic oscillator, on-balance volume (OBV), average directional movement index (ADX), and simple moving averages (3-day moving average, 5-day moving average, 10-day moving average, 14-day moving average, 20-day moving average, 22-day moving average, 50-day moving average, 100-day moving average, 200-day moving average). In this regard, we combined these two techniques and obtained a hybrid intelligence method. By applying this hybrid model to each of these indicators, we forecast the movements of the Borsa Istanbul (BIST) 30 index. The experimental result indicates that our best proposed hybrid model has a successful forecast rate of 75%, which is higher than the single ANN or GA forecasting models.

Detection of water bodies and their flow paths is elemental process of terrain analysis in any application related with surface water. Several algorithms have been proposed for automatic extraction of surface flow paths from Digital Elevation Models (DEMs) (e.g., O’Callaghan and Mark, 1984; Tarboton, 1997; Paik, 2008). While these algorithms have been widely applied, DEMs-based approaches have fundamental limitation in detecting water bodies. To resolve this issue, we propose a hybrid approach that utilizes DEMs and satellite imagery together. These dataset supplement each other’s weakness, providing extra information for better detection of water bodies and flow paths. The proposed approach is tested for the Geum River, showing successfully extraction of flow boundaries and more resonable flow paths within water bodies.

This paper takes a hybrid approach, combining the time and causality frame approaches to examine the interchangeability between should and must, which are epistemic modal auxiliary verbs that indicate logical inference and deduction. It is argued that only must is used when deduction is temporally situated at the present or in the past and directed from consequences to causes, but only should is used when the same process is situated in the future and directed from causes to consequences. The paper also shows either should or must are used in the remaining two types of cases-that is, those in which the process of deduction regards future situations and moves from effects to causes, and those in which deduction regards present or past situations and moves from causes to effects.

The pollen grain is a unique tricellular structure suitable for the delivery of the sperm cells to the ovule. All nutrients required for microspore and pollen cell growth are derived by passage through the anther locule and secretion by the tapetum lining. During later stages the tapetum degenerates but contributes to produce pigments, waxes, lipids and proteins which form the pollen coat and function in signaling between male (pollen) and female (pistil) tissues. The development of both normal pollen and tapetum is necessary for the fertilization processes in rice and would be exploited for the induction of male-sterility which is very useful to improve economic value of crops. We aredeveloping new approaches using a conditional male-sterility for the F1 hybrid seed production in rice. The conventional three parental systems for F1 hybrid seed production requirethe following three lines: male-sterile line, maintainer line, and restorer line. In this system, a critical requirement is to maintain the male-sterile inbred lines. Here we suggest molecular approaches, in which the engineered male-sterile plants are generated by regulating endogenous hormonal balance through the loss-of-function of genes. We can expect the male-sterility can be restored by exogenous applications of hormones such as gibberellin or jasmonic acid. Based on two parental systems, we will address the answer onfollowing question: how can we maintain a male-sterile line producing 100% male-sterile progenies without a maintainer? This work was supported by grants from Crop Functional Genomics Center of the 21C Frontier Program (CG1517), RepublicKorea.

일반적으로 저수지 최적운영의 목적은 한정된 수자원을 여러 목적으로 최적 분배하여 얻는 이익의 최대화와, 홍수 발생으로 인한 과잉 수량을 안전하게 배제시킴으로써 홍수 취약지역의 피해를 최소화시키는 것으로 구분할 수 있다. 저수지 운영에 대한 연구사를 고찰해 볼 때, 지난 수십 년간 첫 번째 영역에 연구가 집중되었음을 알 수 있다. 본 연구의 목적은, 충주 저수지의 홍수조절을 위한 저수지 최적운영의 방법론 개발에 중점을 두고, 하류 홍수피해 최소화와 댐 안