• Ocean and Polar Research
• /
• v.27 no.2
• /
• pp.125-133
• /
• 2005

This study described the phonology and reproductive potential of four species of Korean seagrasses, Zostera caespitosa, Z. caulescem, Z. Japonica and Z. marina. Z. caespitosa and Z. caulescens sampled from a mixed stand at the subtidal area of Yulpo Bay, Geojedo of the South Sea of Korea in November 2002 and August 2003. Z japonica and Z. marina occurred at the depth between the middle intertidal and shallow subtidal (<1m below mean sea level) of Seungbongdo (in Yellow Sea) samples collected in February and October 2003. The sexual reproductive phase of the four Zostera species was apparently different in timing of flowering, reproductive period, fruiting and seed maturing. Z. caespitosa flowered from February to early May $(10-16^{\circ}C)$, and its seed production completed in early May. The reproductive shoots of Z. caulescens began to appear in January $(9^{\circ}C)$, and its flowering followed from February to June $(10-19^{\circ}C)$. The flowers of Z. japonica were observed from July to September $(18-22^{\circ}C)$, and its seeds matured from August to September. The most commonly I marina flowered from April to August $(7-21^{\circ}C)$ and developed into seeds in July. Z. caulescens, the largest plant, had the highest number of seeds per shoot and longest spadix length. Z. marina, which was intermediate In size, recorded the highest reproductive potential. The study indicates that the reproductive phase and potential of the four species of seagrass from Korea are highly related to water temperature, and the populations of these species show a perennial lifespan with a low sexual reproductive input.

• Journal of Life Science
• /
• v.21 no.1
• /
• pp.102-109
• /
• 2011

The genioglossus muscle plays an important role in maintaining upper airway patency during inspiration; if this muscle does not contract normally, breathing disorders occur due to closing of the upper airway. These occur because of disorders of synaptic input to the genioglossus motoneurons, however, little is known about it. In this study, the distribution of GABA-, glycine-, and glutamate-like immunoreactivity in axon terminals on dendrites of the rat genioglossus motoneurons, stained intracellularly with horseradish peroxidase (HRP), was examined by using postembedding immunogold histochemistry in serial ultrathin sections. The motoneurons were divided into four compartments: the soma, and primary (Pd), intermediate (Id), and distal dendrites (Dd). Quantitative analysis of 157, 188, 181, and 96 boutons synapsing on 3 soma, 14 Pd, 35 Id, and 28 Dd, respectively, was performed. 71.9% of the total number of studied boutons had immunoreactivity for at least one of the three amino acids. 32.8% of the total number of studied boutons were immunopositive for GABA and/or glycine and 39.1% for glutamate. Among the former, 14.2% showed glycine immunoreactivity only and 13.3% were immunoreactive to both glycine and GABA. The remainder (5.3%) showed immunoreactivity for GABA only. Most boutons immunoreactive to inhibitory amino acids contained a mixture of flattened, oval, and round synaptic vesicles. Most boutons immunoreactive to excitatory amino acids contained clear and spherical synaptic vesicles with a few dense-cored vesicles. When comparisons of the inhibitory and excitatory boutons were made between the soma and three dendritic segments, the proportion of the inhibitory to the excitatory boutons was high in the Dd (23.9% vs. 43.8%) but somewhat low in the soma (35.7% vs. 38.2%), Pd (34.6% vs. 37.8%) and Id (33.1% vs. 38.7%). The percentage of synaptic covering of the inhibitory synaptic boutons decreased in the order of soma, Pd, Id, and Dd, but this trend was not applicable to the excitatory boutons. The present study provides possible evidence that the spatial distribution patterns of inhibitory and excitatory synapses are different in the soma and dendritic tree of the rat genioglussus motoneurons.

• The KIPS Transactions:PartA
• /
• v.12A no.2 s.92
• /
• pp.95-102
• /
• 2005

The Newton-Raphson iterative algorithm for finding a floating point reciprocal which is widely used for a floating point division, calculates the reciprocal by performing a fixed number of multiplications. In this paper, a variable latency Newton-Raphson's reciprocal algorithm is proposed that performs multiplications a variable number of times until the error becomes smaller than a given value. To find the reciprocal of a floating point number F, the algorithm repeats the following operations: '$'X_{i+1}=X=X_i*(2-e_r-F*X_i),\;i\in\{0,\;1,\;2,...n-1\}'$ with the initial value $'X_0=\frac{1}{F}{\pm}e_0'$. The bits to the right of p fractional bits in intermediate multiplication results are truncated, and this truncation error is less than $'e_r=2^{-p}'$. The value of p is 27 for the single precision floating point, and 57 for the double precision floating point. Let $'X_i=\frac{1}{F}+e_i{'}$, these is $'X_{i+1}=\frac{1}{F}-e_{i+1},\;where\;{'}e_{i+1}, is less than the smallest number which is representable by floating point number. So, $X_{i+1}$ is approximate to $'\frac{1}{F}{'}$. Since the number of multiplications performed by the proposed algorithm is dependent on the input values, the average number of multiplications per an operation is derived from many reciprocal tables $(X_0=\frac{1}{F}{\pm}e_0)$ with varying sizes. The superiority of this algorithm is proved by comparing this average number with the fixed number of multiplications of the conventional algorithm. Since the proposed algorithm only performs the multiplications until the error gets smaller than a given value, it can be used to improve the performance of a reciprocal unit. Also, it can be used to construct optimized approximate reciprocal tables. The results of this paper can be applied to many areas that utilize floating point numbers, such as digital signal processing, computer graphics, multimedia scientific computing, etc.

• Journal of Korea Water Resources Association
• /
• v.57 no.3
• /
• pp.151-164
• /
• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.