Earticle

This paper proposes a novel fractional frequency reuse(FFR) based on dynamic user distribution. In the FFR, a macro cell is divided into two regions, i.e., the inner region(IR) and outer region(OR). The criterion for dividing the IR and OR is the distance ratio of the radius. However, these distance-based criteria are uncertain in measuring user performance. This is because there are various attenuation phenomena such as shadowing and wall penetration as well as path loss. Therefore, we propose a novel FFR based on dynamic user classification with signal to interference plus noise ratio(SINR) of macro users and classify the FFR into two regions newly. Simulation results show that the proposed scheme has better performance than the conventional FFR in terms of SINR and throughput of macro cell users.

In this paper we study the Minimum Error Discrimination problem (MED) for ensembles of linearly independent (LI) pure states. By constructing a map from the set on those ensembles we show that the Pretty Good Measurement (PGM) and the optimal measurement for the MED are related by the map.

This study used cerium iron hydroxide nanoparticle with HEMA (2-hydroxyethyl methacrylate), the cross-linker EGDMA (ethylene glycol dimethacrylate), NVP (N-vinyl-2-pyrrolidone) and the initiator AIBN (azobisisobutyronitrile) for copolymerization. Also, the physical properties of the prepared lenses were compared, and their applicability as polymers for ophthalmic materials was experimented. The results of the measurement showed that the UV blocking rate and the wettability increased with the cerium iron hydroxide nanoparticles addition ratio, and the refractive index and water content were not affected. Thus, the produced copolymer is expected to be useful as a functional contact lens material while satisfying the basic physical properties of the hydrogel contact lens.

In this paper, we study on the reinterpretation of Burnside's theorem that is a tool to compute the number of equivalence classes of a group action on a set, and by applying it, we find out the numbers of different patterns in coloring problems of various types of figures with symmetry and use them for computing the numbers of different kinds of chemical compounds.

The unsustainable human activities like increased use of automobiles, heavy industrialization and the use of large volumes of fertilizers, chemicals and pesticides in the agricultural land cause climate change problems in one way or another. Under normal circumstances, the heat radiations from the sun will be reflected back. An excessive volume of GHGs in the atmosphere would prevent these radiations from reflecting back. East Asia is facing severe climate change issues in recent times. A lot of climate change problems such as hurricanes and floods have been reported from this region in the last couple of decades. The study aimed at investigating the climate change in East Asia with changing Sea Surface Temperature (SST). The study adopted a quantitative research method with a case study research design where a deliberate focus was made on the East Asia Region. Secondary data was gathered and analyzed to yield both descriptive and inferential statistics. The study concluded that the impact of East Asia Climate variability was significant mainly for some extreme events. Also, the study concluded that there was a significant link between the change of the East Asia climate variability and that of the sea surface temperature. Further, the study concluded that a linear relationship existed between the sea surface temperature and the climate of East Asia. Hence, a linear regression was a significant predictor of the East Asia Climate (EAC) based on changing sea surface temperature. The model revealed that 37.4% of the variations in the climate change index were explained by the changes in the sea surface temperature. The climate was expected to change with a value of 49.48 for a unit change in the sea surface temperature.

This study aims to create a model for predicting the number of extinguishment manpower to put out forest fires by taking into account the climate, the situation, and the extent of the damage at the time of the forest fires. Past research has been approached to determine the cause of the forest fire or to predict the occurrence of a forest fire. How to deal with forest fires is also a very important part of how to deal with them, so predicting the number of extinguishment manpower is important. Therefore predicting the number of extinguishment manpower that have been put into the forest fire is something that can be presented as a new perspective. This study presents a model for predicting the number of extinguishment manpower inputs considering the scale of the damage with forest fire on a scale bigger than 0.1 ha as data based on the forest fire annual report(Korea Forest Service; KFS) from 2015 to 2018 using the moderated multiple regression analysis. As a result, weather factors and extinguished time considering the damage show that affect forest fire extinguishment manpower.